INTERCHANGEABILITY OF INFRARED AND C DEVICES ...Interchangeability of Infrared and Conductive...

INTERCHANGEABILITY OF INFRARED AND CONDUCTIVE DEVICES FOR THE MEASUREMENT OF HUMAN SKIN

TEMPERATURE

Aaron James Edward Bach Bachelor of Exercise and Movement Sciences

Submitted in fulfilment of the requirements for the degree of

HL84: Master of Applied Science (Research)

Exercise and Nutrition Sciences

Faculty of Health

Queensland University of Technology

2014

Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature i

Keywords

Conduction, Cutaneous Temperature, Exercise, Exercise Physiology, Infrared,

Radiation, Recovery, Skin Temperature, Thermography, Thermometry,

Thermophysiology, Thermoregulation, Tissue Temperature.

ii Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature

Abstract

The skin is the site of reciprocal heat transfer between the human body and the

external environment. Consequently, the assessment of skin temperature is extremely

important in sports medicine, exercise science, occupational, clinical and public

heath settings. Currently there is no gold standard for the measurement of skin

temperature. The primary methods of measuring 𝑇sk are derived from conductive

(contact) and infrared devices. These techniques apply different scientific principles

of thermal heat transfer. Conductive methods are based upon thermal conduction as a

result of physical contact between the object of interest and the measurement device.

While, infrared devices determine temperature by detecting infrared thermal

radiation being emitted from the skin.

Current practice suggests that for any skin temperature devices to be

considered interchangeable, temperature differences should not exceed the proposed

clinical significant difference of 0.5 °C. This relativity small temperature difference

represents the maximum allowable disagreement between 𝑇sk devices, and any

deviation outside of these limits could produce erroneous data that significantly

influences the conclusions drawn by researchers and clinicians. Unfortunately,

despite widespread use throughout clinical and exercise science settings the scientific

evidence supporting the interchangeability of infrared thermometry with more

traditional conductive instruments is limited and equivocal. Therefore, the purpose of

this thesis was to investigate the interchangeability of conductive and infrared means

of skin temperature measurement under a variety of conditions.

This was conducted through an initial systematic review of the current

literature pertaining to conductive and infrared device interchangeability (Chapter 3).

The key findings of this review was 1) there is no trend for conductive or infrared

devices to consistently overestimate 𝑇sk compared to one another; 2) conductive and

infrared devices are not interchangeable under resting thermoneutral conditions; and

3) that more high-quality studies are needed that compare devices in the presence of

environmental and physical stressors before further conclusions can be drawn

regarding their interchangeability.

In addition to the systematic review, two original investigations were

conducted. The first was to ensure accurate data collection for the primary study via

Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature iii

the calibration of skin temperature measurement devices (Chapter 4) and identify a

comparison device to be used in a subsequent human investigation. Conductive and

infrared devices were calibrated against a certified thermometer in a stirred waterbath

through the expected physiological skin temperature range (11 temperatures between

20 and 42 °C) prior to experimental data collection. A linear regression was

subsequently developed for each device before human testing, allowing for a

correction to be applied following human data collection.

The second investigation (Chapter 5) aimed to answer the primary research

question, are conductive and infrared techniques of skin temperature measurement

interchangeable under a variety of conditions under a variety of conditions? Thirty

healthy males had mean skin temperature measured simultaneously with the four

skin temperature devices used in Chapter 4. Measurements were taken every 3-min

from four regions of interest (neck, scapular, hand and shin) during 30-min of

thermoneutral rest (24.0 ± 1.3 56 ± 9% relative humidity), 30-min of cycle ergometry

in the heat (38.0 ± 0.5 °C, 41 ± 2% relative humidity) and 45-min of thermoneutral

recovery. Systematic errors exceeding statistical (P < 0.05) and clinical (>0.5 °C)

significance were observed between conductive and infrared devices throughout all

conditions. A significant main effect for device, time and their interaction was

observed in all three periods for 𝑇�sk (P < 0.05). Mean differences ± SD between the

thermistor and iButton® (rest, exercise and recovery) were as follows: -0.01±0.2°C, -

0.25±0.42°C, -0.37±0.5°C; thermistor and infrared thermometer: -0.34±0.22°C,

0.46±0.63°C, -1.04±0.89°C; thermistor and infrared camera (rest, recovery): -

0.83±0.39°C, -1.88±0.95°C. Pairwise comparisons of 𝑇�sk revealed significant

differences (P < 0.05) between TM and both infrared devices during resting

conditions, and significant differences (P < 0.05) for comparisons between the TM

and all other devices tested during exercise and recovery. Furthermore, devices that

were within acceptable agreement during rest, failed to be classified as

interchangeable under environmental or external interventions (i.e., exercise in the

heat).

In summary the findings of this thesis suggest that clinical and significant

differences exist between conductive and infrared devices which are commonly

employed in the assessment of human 𝑇sk in exercise science, research and clinical

settings. This has important implications given the wide variety of commercially

iv Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature

available 𝑇sk measurement devices available to the public. Accurate comparisons

between publications using different 𝑇sk measurement methods may not be possible

under resting, exercise and high ambient conditions which depict different

thermoregulatory responses. These significant differences between conductive and

infrared means could potentially influence the interpretation of results, diagnosis and

therefore treatment outcomes for clinical and exercise science applications.

v Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature

Table of Contents Keywords ................................................................................................................................................. i

Abstract .................................................................................................................................................. ii

List of Figures ..................................................................................................................................... viii

List of Tables ......................................................................................................................................... ix

List of Abbreviations .............................................................................................................................. x

Glossary of Terms ................................................................................................................................. xii

Statement of Original Authorship ........................................................................................................ xiv

Acknowledgements .............................................................................................................................. .xv

CHAPTER 1: INTRODUCTION ....................................................................................................... 3 1.1 Background and rationale for research ........................................................................................ 3

1.2 Aim of research ............................................................................................................................ 4

1.3 Objectives of research .................................................................................................................. 4 1.4 Thesis Hypotheses ....................................................................................................................... 4

1.5 Thesis Outline .............................................................................................................................. 5

CHAPTER 2: LITERATURE REVIEW ........................................................................................... 7 2.1 Introduction.................................................................................................................................. 7

2.2 Thermodynamics ......................................................................................................................... 7

2.3 Mechanisms of Heat Exchange in the Human Body ................................................................... 8 2.4 Thermoregulation and Skin Temperature .................................................................................. 10

2.4.1 Rest 10 2.4.2 Exercise .......................................................................................................................... 11 2.4.3 Extreme Environments ................................................................................................... 13

2.5 Mean Skin Temperature ............................................................................................................. 15

2.6 Applications of Skin Temperature MeasurEment ...................................................................... 17 2.7 Characteristics That Influence Human Skin Temperature ......................................................... 20

2.7.1 Inherent ........................................................................................................................... 20 2.7.2 Behavioural..................................................................................................................... 26

2.8 Skin Temperature Measurement Techniques ............................................................................. 29 2.8.1 Conductive Devices ........................................................................................................ 30 2.8.2 Considerations When Using Conductive Devices .......................................................... 31 2.8.3 Infrared Devices ............................................................................................................. 33 2.8.4 Considerations When Using Infrared Devices ................................................................ 35

2.9 Defining Interchangeablilty ....................................................................................................... 37

2.10 Conclusion ................................................................................................................................. 37

CHAPTER 3: ARE CONDUCTIVE AND INFRARED DEVICES FOR MEASURING SKIN TEMPERATURE INTERCHANGEABLE? A SYSTEMATIC REVIEW ................................... 39 3.1 Introduction................................................................................................................................ 39

3.2 Method ....................................................................................................................................... 42 3.2.1 Search Strategy ............................................................................................................... 42 3.2.2 Inclusion Criteria ............................................................................................................ 43 3.2.3 Data Extraction and Management .................................................................................. 43

3.3 Results ....................................................................................................................................... 50 3.3.1 Included studies .............................................................................................................. 50

Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature vi

3.3.2 Detail of Comparisons .................................................................................................... 50 3.3.3 Risk of bias ..................................................................................................................... 51 3.3.4 Study heterogeneity ........................................................................................................ 52 3.3.5 Cold Environment and Cryotherapy ............................................................................... 52 3.3.6 Thermoneutral Environment ........................................................................................... 53 3.3.7 Hot Environment ............................................................................................................ 53

3.4 Discussion .................................................................................................................................. 55 3.4.1 Evaluation of Methodological Quality............................................................................ 55 3.4.2 Summary of Findings ..................................................................................................... 55 3.4.3 Limitations and Future Research .................................................................................... 57

3.5 Conclusions ................................................................................................................................ 57

CHAPTER 4: CORRECTION FORMULA OF INFRARED AND CONDUCTIVE THERMOMETRY .............................................................................................................................. 61 4.1 Introduction ................................................................................................................................ 61 4.2 Methods ..................................................................................................................................... 62

4.2.1 Experimental overview ................................................................................................... 62 4.2.2 Measurement Devices and Procedures ........................................................................... 64 4.2.3 Statistical Analysis.......................................................................................................... 65

4.3 Results ........................................................................................................................................ 66

4.4 Discussion .................................................................................................................................. 70 4.4.1 Limitations and Future Research .................................................................................... 72

4.5 Conclusion ................................................................................................................................. 72

CHAPTER 5: MEAN SKIN TEMPERATURE ASSESSMENT DURING REST, EXERCISE IN THE HEAT AND RECOVERY: DIFFERENCES BETWEEN CONDUCTIVE AND INFRARED DEVICES ....................................................................................................................... 75 5.1 Introduction ................................................................................................................................ 75

5.2 Methods ..................................................................................................................................... 76 5.2.1 Participants ..................................................................................................................... 76 5.2.2 Pre-experimental Protocol .............................................................................................. 77 5.2.3 Experimental Protocol .................................................................................................... 78 5.2.4 Measurements and Equipment: ....................................................................................... 81 5.2.5 Statistical Analysis.......................................................................................................... 86

5.3 Results ........................................................................................................................................ 87

5.4 Discussion .................................................................................................................................. 89

5.5 Conclusion ................................................................................................................................. 94

CHAPTER 6: CONCLUSIONS ........................................................................................................ 95

APPENDICES ..................................................................................................................................... 99 Appendix A Ethics Approval ..................................................................................................... 99 Appendix B Health Screen Questionnaire ............................................................................... 100 Appendix C Informed Consent ................................................................................................ 102 Appendix D Complete graphed data for mean skin temperature and all individual sites ........ 107 Appendix E Complete ANOVA outputs for all sites and conditions ....................................... 117 Appendix F Complete post-hoc paired sample T-test comparisons between all devices ......... 122

REFERENCES .................................................................................................................................. 127

viii Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature

List of Figures

Figure 2.1 The electromagnetic spectrum, depicting various properties including visible light and long-wave infrared radiation ......................................................................................... 34

Figure 3.1. PRISMA flow chart describing the selection and exclusion of articles.............................. 43

Figure 3.2. Included Studies: risk of bias summary. ............................................................................. 50

Figure 3.3. Forest plot, skin temperature comparison for 8 of the 9 included studies: Conductive vs. Infrared, outcome: mean skin temperature difference. # Based upon values derived from publication; * data received from correspondence with first author; C4 = Cervical vertebrae 4; L4 = Lumbar vertebrae 4; T1 = Time 1; ITD = 3000A (Genius, Sherwood IMS, California, USA); ITE = DT-1001 (Exergen, Massachusetts, USA). .......................................................................................................... 52

Figure 4.1. Bland–Altman plot of the certified thermometer and a) thermistor 5; b) iButton® 7; c) infrared thermometer; d) infrared camera across eleven water bath temperatures. Solid black line indicates the mean difference (MD); dashed lines represent the 95% limits of agreement (LoA). ................................................................................................... 66

Figure 5.1. Four skin temperature measurement regions of interest in accordance with International Organisation for Standardisation - 9886. 1) back of neck; 2) inferior border of right scapula; 3) dorsal right hand; 4) proximal third of right tibia. ..................... 77

Figure 5.2. Timeline of data collection protocol. 𝑇�𝑠𝑘 = Mean Skin Temperature; TM = Thermistor; IB = iButton®; IT = Infrared Thermometer; IC = Infrared Camera. ................. 78

Figure 5.3. Example of regions of interest captured via infrared thermography. a) Hand b) Neck and Scapula c) Shin. ................................................................................................... 83

Figure 5.4. a) Diagram of template dimensions used on each of the four skin sites; b) example of the randomised layout of marked and placed devices on a male subject’s shin; IB: iButton®, IT: Infrared Thermometer, TM: Thermistor, IC: Infrared Camera. ...................... 84

Figure 5.5. Mean skin temperature (n=30) of all tested devices during rest (4 devices), exercise (3 devices) and recovery (4 devices). a = IB clinically (>0.5 °C) and significantly (P < 0.001) different from TM; b = IT clinically (>0.5 °C) and significantly (P < 0.001) different from TM; c = IC clinically (>0.5 °C) and significantly (P < 0.001) different from TM. TM: Thermistor; IB: iButton®; IT: Infrared Thermometer; IC: Infrared Camera. ................................................................................................................................ 86

Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature ix

List of Tables

Table 2.1. Commonly used 𝑇�sk formula, including site and weighting. ................................................ 16

Table 2.2. Examples of 𝑇sk changes used to aid in the diagnosis of illness and injury. ....................... 25

Table 3.1. Description of devices .......................................................................................................... 41 Table 3.2. Details of articles included in the systematic review ........................................................... 45

Table 4.1. Device specifications ............................................................................................................ 61

Table 4.2. Mean difference and measures of variation for all tested contact sensors in comparison to the certified thermometer. ............................................................................ 67

Table 4.3. Calibration formula for all devices. ..................................................................................... 68

Table 5.1. Participant characteristics, values are mean ± standard deviation (range). ....................... 75 Table 5.2. Device specifications ............................................................................................................ 80

x Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature

List of Abbreviations

ε Emissivity

∑SKF Sum of Skinfolds

°C Degrees Celsius

µm Micrometres

ANOVA Analysis of Variance

ASTM American Society for Testing and Materials

BM Body Mass

BMI Body Mass Index

CI 95% Confidence Intervals

H0 Null Hypothesis

HSK Net Heat Loss from the Skin

HZ Hertz

IB iButton®

IC Infrared Camera

IT Infrared Thermometer

kg Kilograms

KSK Conduction of Skin

LoA Limits of Agreement

m Metres

MD Mean Difference

mm Millimetres

NIST National Institute of Standards and Technology

nm Nanometres

O2 Oxygen

Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature xi

RH Relative Humidity

SD Standard Deviation

SE Standard Error

Tc Core Temperature

Thand Hand Skin Temperature

TM Thermistor

Tneck Neck Skin Temperature

Troom Room Temperature

Tscapular Scapular Skin Temperature

Tshin Shin Skin Temperature

𝑇sk Skin Temperature

𝑇�sk Mean Skin Temperature

xii Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature

Glossary of Terms

Calibration: A methodical measurement procedure to determine all the parameters

significantly affecting an instrument’s performance.

Emissivity: A dimensionless quality that represents the ratio of infrared energy

radiated by an object at a given temperature and spectral band to the energy emitted

by a perfect radiator (blackbody) at the same temperature and spectral band. The

emissivity of a perfect blackbody is unity (1.00) (Thomas, 2006).

Error: the difference between an observed of calculated value and a true value.

Composed of random (affects reliability) and systematic (affects validity) error.

iButton®: A wireless, self-enclosed and programmable, contact device that stores

temperature values in an internal memory for retrospective extraction (Harper

Smith, Crabtree, Bilzon, & Walsh, 2010).

Infrared (Handheld) Thermometer: Typically a stand-alone, non-contact, point-

and-shoot device that displays a single digital temperature reading by measuring

infrared energy at a localised ‘spot’ area of the skin (Thomas, 2006).

Infrared: The portion of the electromagnetic spectrum extending from the far red,

visible at approximately 0.75 to 1000 µm. However, because of instrument design

considerations all infrared measurements in this thesis were made between 7.5-14µm

(Thomas, 2006).

Infrared Thermal Imaging (Camera): detects infrared energy as a function of

temperature and converts the electronic video signal into an image displayed on a

connected computer, with each pixel representing a single temperature data point.

Interchangeability: the sufficient agreement between two different methods of data

collection, allowing for the substitution of methods without producing significant

measurement differences (Bland & Altman, 1986).

Reliability: the extent to which an experiment, test, or measuring procedure yields

the same results on repeated trails.

Repeatability: the closeness of agreement between the results of successive

measurements carried out under the same conditions of measurement.

Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature xiii

Reproducibility: the closeness of agreement between the results of successive

measurements carried out under changed conditions of measurement.

Temperature: A degree of hotness or coldness of an object measurable by a specific

scale, where heat is defined as thermal energy in transit and flows from objects of

higher temperature to objects of lower temperature (Thomas, 2006).

Thermistor: A surface temperature probe - that requires contact with the object of

interest - uses an internal temperature sensitive resistor that measures temperature by

using a non-linear relationship between resistance and temperature.

Thermography: the product of data collection via an infrared means used to

measure temperature variations on the surface of the body (Blatteis et al., 2001).

Thermometry: the measurement of temperature typically associated with

conductive (contact) devices.

Thermoneutral Temperature: The range of ambient temperature at which

temperature regulation is achieved only by control of sensible heat loss and therefore

is different when insulation, posture or metabolic rate varies (Blatteis et al., 2001).

An example of a thermoneutral temperature for a resting lightly clothed human

would be between 22 and 26 °C (de Dear & Brager, 2002).

Thermoregulation: Maintenance of a constant internal body temperature

independent from the environmental temperature.

Validity: the extent to which a situation as observed reflects the true situation, of the

degree to which data collected by a measure are correct or true.

xiv Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature

Statement of Original Authorship

The work contained in this thesis has not been previously submitted to meet

requirements for an award at this or any other higher education institution. To the

best of my knowledge and belief, the thesis contains no material previously

published or written by another person except where due reference is made.

Signature:

Date: 20/06/2014

QUT Verified Signature

Interchangeability of Infrared and Conductive Devices for the Measurement of Mean Skin Temperature xv

Acknowledgements

There are a number of people without whom this thesis would not have been

written, and to whom I am greatly indebted.

First and foremost, my most sincere thanks must go to my supervisors, Dr.

Joseph Costello and Associate Professor Ian Stewart, both of whom have supported

me above and beyond my expectations.

To my principle supervisor Dr. Joseph Costello, thank you for your patience,

direction and feedback for the duration of my Masters project. Your door was always

open to me whenever I needed your expertise, and I was encouraged after each

discussion with you.

To my associate supervisor Associate Professor Ian Stewart, thank you for the

guidance you have given me both before and throughout my post-graduate research.

Your advice has helped shape the direction in which my academic career is taking. In

addition to the emotional support, I am extremely grateful for your financial

assistance in the form of both a supervisor funded scholarship and employment as a

research assistant throughout my degree.

To my Mum and Dad, thanks for all the patience and encouragement in any

and all of my endeavours. My love and recognition goes to my partner Katrina, for

her unwavering support and perspective throughout my degree, without wanting for

anything in return. I would also like to acknowledge Katrina’s parents, Lex and Jen,

who welcomed me into their home to live during my entire tertiary education and

provided me with the love and support that has contributed to my success.

I would like to thank all of my participants who agreed to be a part of this

project and give a big thank you to both Alice Disher and David Borg. Without their

tireless efforts in assisting with data collection my research would not be possible.

Finally I would like to thank my fellow research students (Alice Disher,

Matthew Bourne) and QUT employees (Brittany Dias, David Borg) for their support

and encouragement throughout my studies.

Chapter 1: Introduction 1

Chapter 1: Introduction

1.1 BACKGROUND AND RATIONALE FOR RESEARCH

Skin temperature (𝑇sk) is an important physiological measure that can reflect

the presence of illness and injury as well provide insight into the localised

interactions between the body and the environment (Lim, Byrne, & Lee, 2008). 𝑇sk is

assessed in exercise science, occupational, surgical, clinical and public heath

settings. The measurements have a wide range of applications that consist of, but are

not limited to, the assessment of thermoregulatory responses (Wang, Zhang, Arens,

& Huizenga, 2007), identification of heat stress and physiological strain (Cuddy,

Buller, Hailes, & Ruby, 2013), evaluation of cryotherapy (Bleakley, Costello, &

Glasgow, 2012; Costello, Culligan, Selfe, & Donnelly, 2012), and the diagnosis of

disease (Wasner, Schattschneider, & Baron, 2002).

Methods of measuring 𝑇sk fall into two categories: conductive and infrared.

Conductive devices require direct contact with the skin and measure temperatures

through heat transfer via conduction (Tyler, 2011). Infrared devices detect emitted

radiation from the skin surface that is proportional to its temperature (Lahiri,

Bagavathiappan, Jayakumar, & Philip, 2012). Despite the differences in scientific

principles underpinning each method, many researchers and clinicians assume

interchangeability between devices under all circumstances.

Current practice suggests that for any other device to be considered

interchangeable temperature differences should not exceed the proposed clinical

significant difference of 0.5 °C (Joly & Weil, 1969; Kelechi, Good, & Mueller, 2011;

Kelechi, Michel, & Wiseman, 2006; Selfe, Whitaker, & Hardaker, 2008). This

relativity small temperature difference represents the maximum allowable

disagreement between 𝑇sk devices, and any deviation outside of these limits could

produce erroneous data that significantly influences the conclusions drawn by

researchers and clinicians. The implications of the current research could aid in the

understanding of which circumstances are most appropriate for conductive and

infrared 𝑇sk measures. Without this research and ensuing understanding of

measurement influences accurate comparisons between published studies using

varying methods may not be possible. Furthermore, the erroneous collection of data

2 Chapter 1: Introduction

could alter the interpretation of results, diagnosis and therefore treatment outcomes

for clinical and exercise science applications.

Existing studies into the interchangeability of devices vary in methodological

quality, are confined to a limited number of devices and were compared

predominantly resting thermoneutral conditions (Buono, Jechort, Marques, Smith, &

Welch, 2007; Burnham, McKinely, & Vincent, 2006; Kelechi et al., 2011; Kelechi et

al., 2006; Korukçu & Kilic, 2009; Matsukawa, Ozaki, Nishiyama, Imamura, &

Kumazawa, 2000; Roy, Boucher, & Comtois, 2006b; Ruopsa, Kujala, Kaarela,

Ohtonen, & Ryhänen, 2009; van den Heuvel, Ferguson, Dawson, & Gilbert, 2003).

The findings from these investigations suggest conductive and infrared devices may

not be interchangeable under resting thermoneutral conditions. However, due to

limited and ambiguous findings it is unclear if conductive and infrared devices are

interchangeable in the presence of internal (e.g. exercise) or environmental stimuli

(e.g. cold/heat exposure).

1.2 AIM OF RESEARCH

The primary aim of this thesis was to investigate the interchangeability of

conductive and infrared means of 𝑇sk measurement at rest in a thermoneutral

environment, during exercise in the heat and recovery.

1.3 OBJECTIVES OF RESEARCH

• To systematically review the literature addressing the interchangeability of

conductive and infrared 𝑇sk devices (Chapter 3).

• To calibrate two conductive and two infrared devices, commonly used in the

assessment of 𝑇sk, against a reference standard in a water bath (Chapter 4).

• To establish the most accurate of these four devices to use as a comparative

reference for the human investigation (Chapter 4).

• To compare and contrast measurements of conductive and infrared devices

during rest, exercise in the heat and recovery in humans (Chapter 5).

1.4 THESIS HYPOTHESES

For the studies completed, the null hypotheses were as follows:

Chapter 1: Introduction 3

Chapter 4: Calibration of infrared and conductive thermometry in a

water bath.

H0: Clinical significant differences (0.5 °C) between each device and the

certified thermometer will not be violated.

H0: Compared to the certified thermometer, the thermistor will be classified as

the most accurate of the four tested devices.

Chapter 5: Evaluation of contact and non-contact thermometry for

the measurement of mean skin temperature during rest,

exercise and recovery.

H0: Clinical significant differences between each device and the identified

reference device will not be violated under any of the tested conditions.

1.5 THESIS OUTLINE

This thesis is comprised of six chapters. Following a brief introduction to the

research topic and an outline of the primary aim and objectives of the thesis in the

current chapter (Chapter 1), a traditional literature review and a systematic review of

the current literature are presented (Chapters 2 and 3, respectively). Chapters 4 and 5

comprise of two original investigations presented in manuscript format. Finally,

Chapter 6 will conclude the findings of this research and recommend future

directions.

Chapter 2: presents a review of the relevant literature pertaining to human

thermoregulation, mechanisms for heat transfer and 𝑇sk application and techniques.

This review identifies the existing research in the broader area of 𝑇sk and is a prelude

for a more specific systematic review on device interchangeability in the subsequent

chapter (Chapter 3).

Chapter 3: systematically reviews the relevant literature on the

interchangeability of conductive and infrared 𝑇sk devices. This review identifies

existing research in the area, appraises the methodological and statistical analyses

used in the individual studies and establishes the significance to exercise science

applications. In addition Chapter 3, section 3.4.3 Limitations and Future Research

proposes a number of areas that warrant further investigation. These

4 Chapter 1: Introduction

recommendations formed the basis for the investigations undertaken as part of this

thesis (Chapters 4 and 5).

Chapter 4: establishes the means in which calibration of 𝑇sk devices can be

achieved in a stirred water bath. Chapter 4 was a preliminary investigation that

helped form the methodology of a comparison study on humans (Chapter 5). By

establishing a means by which to calibrate of 𝑇sk devices in a stirred water bath, data

collected from this investigation allowed for the calculation of calibration

coefficients for devices and identified the most accurate device to use as a

comparative tool in Chapter 5.

Chapter 5: is the product of the preceding chapters, with the investigation of

measurement differences between conductive and infrared devices for the assessment

of mean 𝑇sk in resting, exercise in the heat, and recovery conditions (n=30). Again,

this chapter is heavily influenced by the findings of Chapter 4 and addresses the

shortfalls of the identified literature in Chapter 3.

Chapter 6: summarises the results observed and the research completed

throughout this thesis. The practical implications of these findings are explored and

recommendations for future research are presented.

Chapter 2: Literature Review 7

Chapter 2: Literature Review

2.1 INTRODUCTION

This chapter will give a comprehensive overview into the mechanisms of

human heat exchange, thermoregulation and the importance of skin temperature

(𝑇sk). Further to this, the potential influences of human 𝑇sk and means in which 𝑇sk is

assessed will be examined. The subsequent chapter (Chapter 3) will specifically

compare all current publications regarding the measurement differences between

devices used to assess human 𝑇sk.

2.2 THERMODYNAMICS

Within thermodynamics, a system is classified as an object of interest, for

example a beaker of water, or the human skin. Factors influencing the system are

referred to as surroundings. The surroundings allow for the scientific observation of

the behaviour of the system, which in turn helps us to understand the system’s

properties. The thermodynamic laws that govern the behaviour of a system are

defined below (Atkins, 2010):

The Zeroth Law (Equilibrium): if two systems are in thermal equilibrium

with a third, then the first two systems are in thermal equilibrium with each

other.

The First Law (Conservation of Energy): the change in the internal energy

of a system is equal to the sum of the heat added to the system and the work

done on it.

The Second Law (Entropy): heat cannot be transferred from a colder to a

hotter body within a system without net changes occurring in other bodies

within that system.

The Third Law (Nernst Heat Theorem): it is impossible to reduce the

temperature of a system to absolute zero in a finite number of steps.

In order to quantify the thermodynamic motions of molecules that make up a

system (i.e., heat radiation, particle velocity, kinetic energy), three standard

temperature scales – degrees Celsius, degrees Kelvin and degrees Fahrenheit – have

8 Chapter 2: Literature Review

been established. Degrees Celsius (°C) is the most commonly used unit of

temperature measurement.

Thermal energy (unit = Joules) is the measurement term for the potential and

kinetic energy imparted on a system, by the surroundings, that alters its temperature

(Atkins, 2010). This heat can be transferred via four means of transfer; conduction,

convection, radiation and evaporation. The following section introduces each of

these mechanisms for thermal energy transfer in relation to humans.

2.3 MECHANISMS OF HEAT EXCHANGE IN THE HUMAN BODY

Human beings are classed as homeotherms, i.e., capable of sustaining a stable

body temperature, despite fluctuating ambient temperatures (Sawka, Latzka, Matott,

& Montain, 1998). Homeotherms are made up of two compartments, the inner core

and outer shell, or skin (Bouzida, Bendada, & Maldague, 2009). The inner core is

tightly regulated between 36 and 38 °C, depending on the ambient conditions, to

ensure healthy neurological (M. Kenney, Claassen, Bishop, & Fels, 1998),

musculoskeletal (Sawka & Wenger, 1988) and metabolic function (B. Nielsen,

Savard, Richter, Hargreaves, & Saltin, 1990).

The shell (i.e., skin) is the site of reciprocal heat transfer between the human

body and the external environment. This energy exchange occurs by means of

sensible heat transfer mechanisms (conduction, convection, radiation) and latent heat

transfer (evaporation), which allows the human body to absorb and release thermal

energy into the surrounding environment. When core temperature (Tc) rises, excess

heat energy is transferred from the core to the skin, and subsequently from the skin

into the environment.

Conduction

At a molecular level, conduction refers to the transfer of heat energy that

occurs in all substances (i.e., solid, liquid and gas) between hot, rapidly moving or

vibrating molecules (Lyklema, 2001). These faster (hotter) moving molecules

transfer some heat energy to colder neighbouring particles when they collide.

In the case of human heat transfer, conduction refers to the direct contact

between the body, typically the skin, and another surface. Heat is transferred from

the warmer body, proportionate to the size of the temperature gradient, surface area


of contact, pressure between the two bodies and specific conductivity of the surfaces

(Hardy, Du Bois, & Soderstrom, 1938).

Conduction is the primary means of transferring metabolic heat energy from

the body’s core through to the skin (Keller & Seiler, 1971). As Tc rises as a product

of cellular metabolism, excess heat is transferred via conduction from deeper and

surrounding tissues to the skin surface where it can be transferred into the

environment (Prek & Butala, 2010).

Convection

Convection is the transfer of heat energy through a moving fluid medium (i.e.,

air, water). It can be categorised into two forms: natural and forced. Natural

convection occurs when a heat source (e.g., sun) influences temperature gradients of

a fluid (e.g., air), which in turn sees uneven changes in the densities of the fluid,

causing convection currents to form (e.g., wind; Gebhart & Pera, 1971). Forced

convection occurs when an external source (e.g., fan) generates fluid motion of the

surrounding medium (e.g., air).

The skin is encapsulated by a thin layer of air, independent of ambient

atmosphere, known as the boundary layer (H. Lewis, Foster, Mullan, Cox, & Clark,

1969). The introduction of forced convection through an external source or human

movement disrupts this layer of air and allows heat energy to be transferred from the

skin into the environment; depending upon the velocity of the air, surface area of the

body and the temperature gradient between the skin and the ambient air (Mora-

Rodriguez, Del Coso, Aguado-Jimenez, & Estevez, 2007). As Tc increases

circulatory responses transport warm blood from the core to the periphery,

facilitating the loss of heat at the skin surface via convection.

Evaporation

As Tc rises, or in the presence of rising localised 𝑇sk, the autonomic nervous

system stimulates endocrine sweat glands to secrete sweat along the skin surface

(Nadel, Mitchell, & Stolwijk, 1973). This response allows the release of heat energy

through the diffusion of sweat from the skin surface, in addition to water vapour as a

by-product from respiratory breathing (Mora-Rodriguez et al., 2007). The

effectiveness of this evaporative heat loss is proportionate to the water pressure

gradient between the skin and the environment (i.e., relative humidity), the amount


of moisture present on the skin surface and the convection immediately adjacent to

the skin (Wenger, 1972). The wiping away or dripping of sweat should be avoided

where possible, as it provides no evaporative cooling yet contributes to total body

water losses.

Radiation

Thermal radiation is the electromagnetic radiation emitted by all particles with

a temperature greater than absolute zero; with higher temperatures corresponding to

greater radiation emission (Jones, 1998). Emissivity is the term used to describe the

amount of absolute radiation energy released from an object’s surface relative to an

ideal black body (E. Ng, 2009). By knowing the emissivity coefficient of an object’s

surface, infrared devices are able to detect the object’s surface temperature, which is

a product of the energy being released by the object (Modest, 2013). This concept

will be discussed in greater detail in the subsequent sections (see 2.7.3 Infrared

Devices).

2.4 THERMOREGULATION AND SKIN TEMPERATURE

Healthy thermoregulation in humans requires heat balance to be maintained

through the control of physiological mechanisms (sweating, shivering,

vasoconstriction and vasodilation) that balance heat produced within the body and

heat transfer with the environment. Exercise and/or exposure to a colder/hotter

environment disrupt heat balance within the body. Heat balance can be depicted in

the following equation (International Organisation for Standardisation, 2004a):

M - W = Cres + Eres + K + C + R + E + S

where M equals metabolic rate, W is the effective mechanical power ; Cres and

Eres are the convective and evaporative heat exchanges from breathing; K, C, R and E

are the heat exchanges at the skin by conduction, convection, radiation and

evaporation respectively, and S is the remaining heat storage accumulating in the

body.

2.4.1 Rest

At rest, in thermoneutral conditions, metabolic energy production must equal

the heat loss to the surrounding environment to prevent an elevation in Tc. Up to 70%

of the energy used in human metabolism is lost as heat energy, which at rest equates


to approximately 5 Kcal·min-1 (Sawka & Wenger, 1988). During exercise, this heat

energy produced as a by-product of metabolism can increase up to 20 times (Nadel,

Wenger, Roberts, Stolwijk, & Cafarelli, 1977). Temperature receptors located within

the hypothalamus, spinal cord, skin and some abdominal organs monitor temperature

changes, and work on a negative feedback loop to initiate heat lose through

endocrine sweat activation or blood vessel control (vasodilation) (Cabanac, 1975).

Consequently, 𝑇sk is the cumulative total of a number of factors such as the blood

flow at the surface of the skin, heat conduction from deeper tissues, including

muscle, heat loss from evaporation along the skin as well as the influence of any

environmental thermal loads (Prek & Butala, 2010). Under resting conditions, 𝑇sk

distribution across the body sees cooler temperatures at the extremities in comparison

to more proximal sites (e.g., chest); with differences greatest in colder conditions and

a more uniform distribution in hotter ambient temperatures (Webb, 1992). The

autonomic responses and physiology behind thermoregulation during exercise or

extreme environments is outlined in the following sections.

2.4.2 Exercise

During exercise the body produces a rise in metabolic activity and therefore

thermal energy. In response, thermoregulatory mechanisms of heat loss are enacted

to dissipate this excess heat from the body. Even in extreme environmental

conditions the body is able to maintain this thermal equilibrium for long periods of

time, known as compensable heat loss. If the body’s ability to lose heat through the

skin surface is impaired, via excessive clothing, high relative humidity and/or high

ambient temperatures, heat generation during exercise sees a continual rise in Tc (i.e.,

hyperthermia). When evaporation, convection and conduction are unable to match

heat gain, the potential for heat illness and injury rises (Kulka & Kenney, 2002). This

unsustainable shift in heat balance is referred to as uncompensable heat stress.

Exertional heat stroke occurs when Tc exceeds 40 °C, accompanied with central

nervous system dysfunction (Binkley, Beckett, Casa, Kleiner, & Plummer, 2002). If

not treated correctly the resultant heat stroke can progress from disorientation and

irritability, vomiting and diarrhoea, to loss of consciousness, and in severe cases even

death (Bouchama & Knochel, 2002).

Heat illness in sport has led to player deaths in the National Football League,

competitive marathon running, US collegiate and high school sports (Maron, Doerer,


Haas, Tierney, & Mueller, 2009; Mathews et al., 2012; Mueller & Colgate, 2013).

Currently heat stress is the leading cause of sudden death in US high school athletes

(Kerr, Casa, Marshall, & Comstock, 2013; Mueller & Cantu, 2010), and the greatest

external cause of sudden death in US collegiate and high school athletes (Maron et

al., 2009); American Football has greater than ten times the risk of heat illness than

the average rate of all other sports (Kerr et al., 2013; Yard et al., 2010) and has led to

133 deaths in American Footballers between 1931 and 2012 (Mueller & Colgate,

2013). This has been attributed to the increased metabolic production from wearing

protective equipment in addition to impairing heat loss capacity across the skin

surface causing uncompensable heat gain (Kulka & Kenney, 2002).

During compensable steady state endurance exercise, metabolic heat

production as a bi-product of skeletal muscle contraction sees rapid increases in Tc,

before smaller rates of change form a steady plateau, signalling thermal balance. This

Tc elevation is independent of environmental surroundings and proportional to

metabolic rate within an ambient temperature range of 10 to 35 °C (Lind, 1963; M.

Nielsen, 1938). In contrast, initial increases in 𝑇sk while exercising in the heat are

predominantly a function of ambient temperature and are not significantly dependent

upon workload (Stolwijk & Hardy, 1966). Moreover, 𝑇sk increases in response to

warm environments (~30 °C) are governed by increases in vascular blood flow, and

lag behind Tc changes in order to facilitate heat conductive loss between the hotter

core compartments to the cooler skin (Lim et al., 2008). The Tc to mean skin

temperature (𝑇�sk) gradient (Tc - 𝑇�sk) is a reflection of the body’s conductive rate – the

ability transfer heat via blood from the core to the skin. As 𝑇�sk increases, autonomic

activation of sweat response sees linear increases in evaporative cooling at the skin

(Gagge & Gonzalez, 1996). Consequently, this evaporative heat loss at the skin is

closely associated with the skin’s thermal conductance. Skin thermal conductance

(KSK) equates to the net metabolic heat loss from the skin (HSK) divided by the core to

skin temperature gradient (Tc - 𝑇�sk); represented as KSK = HSK / (Tc - 𝑇�sk). Kraning

and Gonzalez (1991) examined thermoregulatory responses, including Tc to 𝑇sk

gradients, during intermittent exercise in the heat (30 °C) under compensable and

uncompensable (encapsulated chemical suits) heat stress. Intermittent exercise

comprised of 10-min episodes of walking (4-min), running (2-min) and seated rest (4

min). In both groups, were greatest during running and lowest during rest. However,


a notable reduction in the Tc - 𝑇�sk gradient and therefore heat loss capacity, was seen

during uncompensable heat stress compared to compensable. This was reflected in

higher 𝑇�sk as a result of encapsulating clothing which impaired the rate of heat

transfer via conduction from the core to the skin.

2.4.3 Extreme Environments

Similar to exercise induced heat gain, hot environments alone initiate anterior

hypothalamus control of nerve impulses to activate blood vessel vasodilation and

sweating responses to remove excess body heat (Rowell, 2011). This vascular and

sweating reaction can also be activated at localised sites detecting 𝑇sk increase (e.g.,

application of a heat pack; Nadel, Bullard, & Stolwijk, 1971; Randall, 1946).

Overall, fluctuations in Tc tend to have greater influence on autonomic responses to

maintain heat balance than that of 𝑇sk (Simon, Pierau, & Taylor, 1986). However,

thermal comfort within an environment and therefore behavioural thermoregulation,

have been shown to be heavily influenced by 𝑇sk (Frank, Raja, Bulcao, & Goldstein,

1999). Changes in surrounding ambient conditions are detected more readily by skin

thermoreceptors that serve to initiate behavioural responses such as seeking warmth,

prior to the recruitment of more metabolically costly reactions (i.e., shivering). The

activity of nerve fibres responding to cold, cold-pain, heat and heat-pain along the

skin surface are published in Guyton and Hall (2000) (Figure 48-10).

In fluctuating environmental temperatures the skin is more responsive to

changes towards colder temperatures due to as many as 10 times the amount of cold-

sensitive nerve endings (Guyton & Hall, 2000). Cold-sensitive temperature signals

originating from thermoreceptors converge while ascending through the spinal cord,

before diverging to multiple brain areas including the midbrain raphe nuclei, reticular

formation and posterior hypothalamus (Burstein, Cliffer, & Giesler, 1987). The

responses evoked (i.e., shivering and vasodilation) are dependent on the amount and

location of cooling, the baseline 𝑇sk and the sum area of the cooled skin (Van

Someren, Raymann, Scherder, Daanen, & Swaab, 2002). Sympathetic stimulation

prompts vasoconstriction of blood vessels to direct blood supply away from the skin,

reducing heat loss into the environment. Concomitant to this, if required – primarily

via Tc changes – hormonal messengers (i.e., norepinephrine) are released from the

medulla to commence involuntary muscle shivering to produce additional metabolic


heat (Cheng et al., 1995). During prolonged cold stress intermittent vasodilation of

extremities, such as the hands, increases blood flow and subsequent 𝑇sk of the finger

tips, which is then followed by another period of vasoconstriction. This process is

repeated and is known as ‘the hunting reaction’ (T. Lewis, 1930) or cold induced

vasodilation (Flouris & Cheung, 2009). The exact reasons for this reaction occurring

are unknown. However, it has been proposed that the increased temperature due to

vasodilation helps reduce cold-related injury (i.e., frostbite; Wilson & Goldman,

1970) and/or maintain manual dexterity and tactile sensitivity (Daanen, 2003).

Variables which make up the surrounding environment such as air temperature,

radiant temperature, wind speed and relative humidity influence the effectiveness of

heat loss mechanisms (i.e., conduction, evaporation etc.) employed by the human

body and as a result can disrupt heat balance of an individual. For the purpose of this

literature review, particular attention will be paid to the influence of hot

environments on human heat exchange.

High ambient temperatures alter the thermal gradient between the skin and the

environment. Once ambient temperatures exceed that of 𝑇sk, conductive and

convective cooling of the skin no longer is achievable, resulting in the ambient

conditions imposing conductive and convective heating of the skin (Prek & Butala,

2010). Similarly, environmental heat gain will progress if radiant temperatures of

surrounding objects exceed 𝑇sk. Thermoregulatory processes overcome this obstacle

by initiating a sweating response to dissipate heat through unidirectional evaporative

cooling. However, evaporative cooling is inversely related to the level of water

vapour (humidity) in the air at a given ambient temperature. In a hot environment,

evaporation plays an important role in dissipating excess body heat, as smaller

differences between the skin and ambient air blunt the heat exchange from

convective and radiative means (Prek & Butala, 2010). Where ambient temperatures

exceed 𝑇sk, cutaneous and respiratory evaporation can account for >80% of heat loss,

as the human body absorbs conductive and convective heat energy from the

environment (L. Armstrong & Maresh, 1993). If water vapour in the ambient air

continues to rise the evaporative cooling rate would slow. Once relative humidity

reaches 100%, sweat and therefore heat energy does not evaporate from the skin (W.

Kenney, DeGroot, & Alexander Holowatz, 2004).


2.5 MEAN SKIN TEMPERATURE

Due to the difficulties associated with measuring the temperature of the entire

skin surface, 𝑇�sk provides a single temperature value derived from temperatures

taken at various sites in respect to a specific formula. 𝑇�sk formulas typical use

weighting factors corresponding to the contribution a particular site makes to the skin

surface area or thermal sensitivity. Formula differ in the total number of sites

measured and weighting factors given to the site, with some formulas varying

between universal weighting (Burton, 1935; Ramanathan, 1964), variable weighting

(Park et al., 1988; Winslow, Herrington, & Gagge, 1936), or no weighting (Mitchell

& Wyndham, 1969; Stolwijk & Hardy, 1966). An explanation of a general formula

for 𝑇�sk is represented below:

𝑇�sk = (ω1·T1) + (ω2·T2) + … + (ωn·Tn)

Where T represents the measured temperature at a given site; ω is the formula

weighting factor. Numerous formulas have been established to estimate 𝑇�sk, ranging

from 3 (Burton, 1935) to 15 (Mitchell & Wyndham, 1969) measurement sites (Table

2.1). 𝑇�sk is predominantly used in exercise science applications, and when coupled

with other physiological measures of exercise such as heart rate and core body

temperature, an evaluation of physiological strain and whole body temperature can

be made (Colin, Timbal, Houdas, Boutelier, & Guieu, 1971; Cuddy et al., 2013).


Table 2.1.

Commonly used 𝑇�sk formula, including site and weighting.

Region Head Trunk Upper Arm Forearm Hand Thigh Calf Foot

Formula Sites Forehead Cheek Neck Chest Abdomen Scapula Sub-scapula Lumbar Posterior Antero-

lower Anterior Posterior Dorsal Anterior Antero-medial

Postero-medial

Postero-lower Anterior Posterior Dorsal

W

Burton[1] 3 0.5 0.14 0.36

Olesen[2] 3 0.5 0.14 0.36

ISO-9886[3] 4 0.28 0.28 0.16 0.28

Ramanathan[4] 4 0.3 0.3 0.2 0.2

Newberg[5] 4 0.34 0.15 0.33 0.18

Houdas[5] 5 0.07 0.175 0.175 0.19 0.39 `

Palmes/Park[6] 6 0.14 0.19 0.19 0.11 0.05 0.32

Hardy/DuBois[7] 7 0.07 0.35 0.14 0.05 0.19 0.13 0.07

Gagge/Nishi[8] 8 0.07 0.175 0.175 0.07 0.07 0.05 0.19 0.2

Nadel[9] 8 0.21 0.1 0.17 0.11 0.12 0.06 0.15 0.08

Crawshaw[11] 8 0.19 0.08 0.12 0.09 0.13 0.12 0.12 0.15

Houdas/Colin[5] 10 0.2 0.05 0.125 0.2 0.05 0.05 0.05 0.125 0.075 0.075

Colin/Houdas[5] 10 0.06 0.12 0.12 0.12 0.08 0.06 0.05 0.19 0.13 0.07

Mitchell[6] 10 0.1 0.125 0.125 0.07 0.07 0.06 0.125 0.125 0.15 0.05

Hardy/DuBois[6] 12 0.07 0.0875 0.0875 0.0875 0.0875 0.14 0.05 0.095 0.095 0.065 0.065 0.07

UW

Stolwijk[11] 10 1/10 1/10 1/10 1/10 1/10 1/10 1/10 1/10 1/10 1/10

Mitchell[6] 15 1/15 1/15 1/15 1/15 1/15 1/15 1/15 1/15 1/15 1/15 1/15 1/15 1/15 1/15 1/15

W = weighted formula; UW = unweighted formula; ISO = International Organisation for Standardisation. [1] = (Burton, 1935); [2] = (Olesen, 1984); [3] = (International Organisation for Standardisation, 2004b); [4] = (Ramanathan, 1964); [5] = (Houdas & Ring, 1982); [6] = (Mitchell & Wyndham, 1969); [7] = (Hardy et al., 1938); [8] = (Gagge & Nishi, 1977); [9] = (Nadel et al., 1973); [10] = (Crawshaw, Nadel, Stolwijk, & Stamford, 1975); [11] = (Stolwijk & Hardy, 1966)


2.6 APPLICATIONS OF SKIN TEMPERATURE MEASUREMENT

Even before the invention of temperature measurement instruments, the

relationship between localised human temperature and pathologies were identified.

As early as 400 BC, the first documented cases of temperature-related conditions

such as fever, involved subjective diagnosis through touching the skin to identify any

temperature differences (Tan, Ng, Rajendra Acharya, & Chee, 2009). In 1868, Carl

Wunderlich invented the clinical thermometer (Ring, 2007). This led the way for the

invention of modern adaptations currently used to assess of human temperature

throughout medicine, exercise science, occupational and research settings.

Exercise Science

Despite substantial research into the larger field of whole-body

thermophysiology, rates of reported thermal illness and injury are on the rise

(Nelson, Collins, Comstock, & McKenzie, 2011). Between 1997 and 2006, an

estimated 54,983 patients were treated for heat-related injury and illness by United

States emergency departments (Nelson et al., 2011). A worrying trend was noted

with the heat injury-illness rates per 100,000 people more than doubling between

1997 (1.2) to 2006 (2.5); with over three-quarters of incidents during this period a

result of participation in sport or exercise. As a result, 𝑇sk is of interest in exercise

and sports medicine as it provides insight into the relationship between the human

body and the surrounding environment. The most popular use of 𝑇sk in exercise

science is the use of 𝑇�sk as an important outcome variable during exercise or testing

in extreme environments. 𝑇sk has been used as the primary measurement outcome in

recent novel exercise science investigations in the identification of delayed onset

muscle soreness (Al-Nakhli, Petrofsky, Laymon, & Berk, 2012) and the

quantification of aerobic and functional performance (Al-Nakhli, Petrofsky, Laymon,

Arai, et al., 2012; Bleakley et al., 2012; Sawka, Cheuvront, & Kenefick, 2012).

Another important application of 𝑇sk assessment in exercise science is during

cryotherapy, or therapeutic tissue cooling. Cryotherapy has become a popular

modality for athletes to improve recovery times following exercise (Costello,

McInerney, Bleakley, Selfe, & Donnelly, 2012), and can be implemented through a

variety of techniques including, but not limited to, cold water immersion, cold air

and ice packs. It has been proposed that a reduction in tissue temperature of at least


12 °C is needed before cryotherapy provides any analgesic effect (Bleakley &

Hopkins, 2010). However, no safe lower limit for 𝑇sk has been established resulting

in reported cases of cold rash (Dover, Borsa, & McDonald, 2004), ice burn (Selfe,

Hardaker, Whitaker, & Hayes, 2007) and nerve damage (Moeller, Monroe, &

McKeag, 1997). These potential risks associated with tissue cooling has seen thermal

imaging become the preferred 𝑇sk measure, because of its superior data collection

across the entire area of interest compared to the spot measurements of more

traditional contact devices (Hardaker et al., 2007).

Occupational

Occupational settings that present high thermal loads run the risk of decreased

productivity and employee safety. Therefore, the standardisation of safety limits for

the maximum physiological temperatures of core and skin have been set to 39.5 and

43 °C respectively (International Organisation for Standardisation, 2004b). Industries

with the greatest risks of exposing workers to high thermal loads include

manufacturing (Fogleman, Fakhrzadeh, & Bernard, 2005), agriculture (Jackson &

Rosenberg, 2010), mining (Hunt, Parker, & Stewart, 2012), emergency services

(Bourlai, Pryor, Suyama, Reis, & Hostler, 2012), construction (Lundgren, Kuklane,

Gao, & Holmer, 2013) and participation in the armed forces (Carter III et al., 2005).

Further to this, studies observing manufacturing injury rates have reported a

significantly greater number of injuries when workplace temperatures exceed 32 °C

(Fogleman et al., 2005) and 42 °C (Nag & Nag, 2001).

In Australia, the cost of work-place injuries and illness as a result of exposure

to Heat, Radiation or Electricity during 2008-2009 in Australia was estimated to be

$1.3 billion (Safe Work Australia, 2012). Studies implementing physiological

measures such as Tc and 𝑇sk assessment have developed and advocated successful

strategies to be implemented in workplaces to help reduce the risks of heat illness

and injury including; self-pacing (Brake & Bates, 2002; Gun & Budd, 1995), work-

rest cycles (Mairiaux & Malchaire, 1985), employee hydration education (Brake &

Bates, 2003) and safety standards for environmental conditions (International

Organisation for Standardisation, 2004a).

In cold environments, the estimated required clothing ensemble and the

corresponding thermal insulation needed for safe exposure times at a given

temperature and wind speed are standardised in ISO 11079 (International


Organisation for Standardisation, 2007). Those recommendations are provided to

maintain homeostatic Tc and 𝑇sk. If clothing is inadequate, the criteria for cessation

of cold exposure in the workplace has been set at a 3 °C fall in 𝑇�sk below

comfortable thermoneutral levels (𝑇�sk ≈34 °C; International Organisation for

Standardisation, 2007, 2009). Localised 𝑇sk limits have been addressed in ISO 11079

(International Organisation for Standardisation, 2007), which recommends the

wearing of gloves and regular monitoring of finger temperatures in cold workplaces

to ensure temperature limits >24 °C are preserved to allow for adequate hand

function. Falls below this finger 𝑇sk could see a loss in dexterity, strength and

coordination increasing the risk for incidence and injury. Further information

regarding the predicted time requirements for the development of pain, numbness

and frostbite as a result of conductive heat loss by touching various materials at a

range of temperatures can be found in ISO 13732/3 (International Organisation for

Standardisation, 2005).

Research has also been conducted into the ergonomic environment of office

workers and associated risks of overuse injury. Gold, Cherniack, and Buchholz

(2004) successfully detected 𝑇sk reductions in the hand following a nine-minute

typing exercise in office workers, potentially leading to a more effective way of

detecting the onset of overuse injuries such as tendinitis and carpal tunnel through

the presence of oedema, inflammation and associated heat.

Clinical

The measurement of 𝑇sk is particularly valuable in the screening, prevention

and diagnosis of various pathologies in unhealthy populations. In clinical settings,

𝑇sk examination has a wide range of applications including breast cancer detection,

diabetic neuropathy and vascular disorders, ocular diseases, dental diagnosis,

inflammatory and osteo-arthritis monitoring. Recent reviews by Ring and Ammer

(2012) and Lahiri and colleges (2012) provide a thorough overview of use of 𝑇sk

measurement in a clinical setting.

Public Health

In the wake of sever acute respiratory syndrome (SARS), swine influenza and

other infections pandemic fevers, non-contact infrared techniques have been widely

used by government health organisations to screen large populations for signs of


fever by measuring face and neck temperatures (Ring & Ammer, 2012). In some

cases this screening measure has been shown to be an effective tool for fast and non-

contact mass screening of fever (Chiang et al., 2008; Chiu et al., 2005; Nguyen et al.,

2010). However, there has been a documented failure of infrared cameras to

successfully identify febrile individuals because of influences by a large number of

individual and environmental factors; such as perspiration, cosmetic make-up, wind

drafts, ambient temperatures and subject to sensor distance (Bitar, Goubar, &

Desenclos, 2009; Ring & Ammer, 2012). This has led to some authors to suggest that

infrared screening may only serve as an alternative Tc measurement tool (Chan,

Cheung, Lauder, & Kumana, 2004) or should be replaced by conductive measures

(Liu, Chang, & Chang, 2004). Regardless, the International Organisation for

Standardisation has developed a set of international standards to help enable the

reliable and reproducible use of infrared cameras for mass screening of fever

(International Organisation for Standardisation, 2007).

2.7 CHARACTERISTICS THAT INFLUENCE HUMAN SKIN TEMPERATURE

Human 𝑇sk is a dynamic physiological response to the surrounding

environment. There are however other inherent and behavioural characteristics that

influence an individual’s 𝑇sk. Where possible these factors should be controlled for

the accurate and reliable measurement of human 𝑇sk. The following section will

outline a number of these characteristics which can be divided into two sub-groups:

1) Inherent – personal characteristics in which there is little or no control over;

and

2) Behavioural – habitual and behavioural factors that can be altered.

2.7.1 Inherent

When evaluating 𝑇sk, intrinsic biological and anatomical factors need to be

taken into consideration. It is impossible to control many of these inherent

characteristics, though it is important to understand their effects on 𝑇sk.

Sex

Many thermophysiology studies avoid recruiting female participants due to

temperature fluctuations associated physical and hormonal differences when

compared to men (Kaciuba-Uscilko & Grucza, 2001). Sexual dimorphism of


anthropometrical characteristics has been cited for thermoregulatory and 𝑇sk

differences between males and females. In cold conditions, female 𝑇�sk is up to 0.5 °C

lower than that of male counterparts (McArdle, Toner, Magel, Spinal, & Pandolf,

1992) and up to 0.7 °C lower in hot conditions (Bittel & Henane, 1975); due to larger

body surface to mass ratio, smaller total and lean body mass and a lower resting

metabolic heat production compared to men (Arciero, Goran, & Poehlman, 1993;

Cortright & Koves, 2000). Interestingly, in a study of lean and obese men matched

for subcutaneous and total body fat but differed in body mass and morphology, found

no significant difference in 𝑇sk between groups during 120-min cold water

immersion (18 °C; Glickman-Weiss et al., 1993). These findings suggest that other

factors such as metabolic rate via lean mass differences and hormonal responses have

a greater influence on 𝑇sk between sexes than morphology.

There have been numerous investigations into the influence that hormonal

changes, particularly throughout the menstrual cycle, have on thermoregulatory

processes in females (Hirata et al., 1986; Horvath & Drinkwater, 1982). Tc

fluctuations have been noted in females using oral contraceptives (hotter

temperatures), during the luteal (hotter temperatures) and the follicular phases

(colder temperatures) of menstruation relative to men (see Figure 2 published in - F.

Baker & Driver, 2007). Hotter temperatures during the luteal phase are most likely

mediated by the hormone progesterone (Rothchild & Barnes, 1952) which alter the

output of thermosensitive neurones in the hypothalamus responsible for temperature

regulation (Nakayama, Suzuki, & Ishizuka, 1975).

Female 𝑇sk is lowest during the follicular phase as a result of reductions in

peripheral blood flow in association with lower Tc (Bartelink, Wollersheim,

Theeuwes, Van Duren, & Thien, 1990; Frascarolo, Schutz, & Jequier, 1992;

Hessemer & Bruck, 1985). Despite these findings, in the presence of exercise no

differences in 𝑇sk have been observed between phases (Pivarnik, Marichal, Spillman,

& Morrow, 1992). Pivarnik et al. (1992) found that during 60-min of endurance

cycle ergometry in thermoneutral conditions oxygen uptake, sweat loss and 𝑇sk were

not influenced by cycle phase. However, Tc, cardiovascular strain and perceived

exertion were all adversely affected during the luteal phase. Fluctuations in hormone

levels in pre and post-menopausal women reduces thermoregulatory control of

vasodilation and in turn sees falls in skin blood flow and therefore 𝑇sk (Brooks et al.,


1997; Charkoudian, Stephens, Pirkle, Kosiba, & Johnson, 1999). Oestrogen

supplementation and hormone therapies have been postulated to increase skin blood

flow and 𝑇sk via increased vasodilation of subcutaneous vessels by stimulating nitric

oxide-dependent vasodilation (Charkoudian et al., 1999). Although, numerous

studies into the effectiveness into this treatment have yielded mixed results (Gilligan,

Badar, Panza, Quyyumi, & Cannon, 1994; Sudhir, Esler, Jennings, & Komesaroff,

1997).

Age

Metabolic and circulatory changes associated with increasing age have often

been suggested as causative factors for thermoregulatory reductions (Petrofsky et al.,

2006). Indeed, studies of 𝑇sk in the elderly show comparative differences to younger

participants (Niu et al., 2001). For example, Niu et al. (2001) tested the 𝑇sk of 57

participants, ranging from 20-88 years and found subjects over 60 years old had

lower 𝑇sk than their younger counterparts. These differences were more pronounced

in the extremities and most likely as a result of impaired circulation capacity during

advancing age. Other studies have also observed age-related diminishing of

vasoconstrictive and vasodilative responses of subcutaneous blood vessels as well as

a decline in sympathetic nerve activity (Holowatz & Kenney, 2010; W. Kenney &

Armstrong, 1996). These adaptations are evident in the elderly who have higher rates

of hypothermia during surgery (Vaughan, Vaughan, & Cork, 1981) and take longer

to rewarm following surgery (Frank et al., 1992). Raymann, Swaab, and Van

Someren (2007) have also documented the inverse relationship between age and

physiological measures such as 𝑇sk, Tc, circadian rhythm and sleep-onset latency.

Although normative Tc for various age groups have been identified (Chamberlain,

Terndrup, Alexander, Silverstone, & Wolf-Klein, 1995), there is currently no defined

normative 𝑇sk range for respective age groups. Further research into these ranges

could allow for more accurate comparisons of the literature and help better

understand the relationship between thermoregulatory deficits and age.

Body Composition

Consideration must be given to what effect excess adiposity has on human 𝑇sk.

In an investigation by Frim, Livingstone, Reed, Nolan, and Limmer (1990) it was

indicated that the distribution of subcutaneous fat influenced measurement error

when calculating 𝑇sk, by altering heat transfer between the core and the skin. Obese


individuals have been identified as having a lower 𝑇sk compared to leaner

participants (LeBlanc, 1954; Livingstone, Nolan, Frim, Reed, & Limmer, 1987;

Savastano et al., 2009). These 𝑇sk differences are greatest in cooler ambient

conditions and decrease as ambient temperature rises (Livingstone et al., 1987).

These findings are not totally unexpected given the impaired vasomotor control seen

in obese populations during changes in Tc (Kasai, Hirose, Matsukawa, Takamata, &

Tanaka, 2003; Meyer, Kundt, Steiner, Schuff-Werner, & Kienast, 2006). In addition,

resting metabolic heat production is significantly higher in the obese compared to

lean individuals due to the greater lean mass (i.e., muscle) that accompanies obesity

(Prentice et al., 1986). The insulating characteristics of fat also prevent efficient heat

loss from the skin into the environment. The influences of fat mass are attributed to a

reduction in thermal conductivity between the core and the skin (Cooper & Trezek,

1971; Lipkin & Hardy, 1954) and are proportional to the degree of obesity (P. Baker

& Daniels, 1956; Jéquier, Gygax, Pittet, & Vannotti, 1974). Furthermore, as

cutaneous heat loss, and the resultant 𝑇sk, is proportional to the total skin surface area

(Sessler, McGuire, & Sessler, 1991), than increases in weight (fat gain) without

relative increases in height will see a reduction in the surface area to total body mass

ratio (Verbraecken, Van de Heyning, De Backer, & Van Gaal, 2006). Therefore, any

change in body composition resulting in greater fat-mass promotes the retention of

body heat and slows the rate of metabolic heat loss (Kurz, Sessler, Narzt, Lenhardt,

& Lackner, 1995), which is reflected in cooler cutaneous temperatures where high

amounts of subcutaneous fat is present (Savastano et al., 2009).

Circadian Rhythm

Human sleep regulation is controlled by a biological circadian rhythm that

adjusts a variety of physiological variables over a 24-hour cycle (Hasselberg,

McMahon, & Parker, 2013). Of most importance to sleep/wake researchers is the

accurate measurement of diurnal oscillation of Tc and 𝑇sk. Independent of exercise Tc

can fluctuate within a range of 1.3 °C in young men (Vitiello et al., 1986) with

amplitudes as low as 0.7 °C depending on age (Rosenthal et al., 1990). Moreover,

because heat loss at the skin is directly related to changes in Tc, 𝑇sk has been shown

to be a reliable measure of circadian system status (Sarabia, Rol, Mendiola, &

Madrid, 2008). The absolute 𝑇sk changes over a daily cycle vary between the

different regions of the body being measured (Krauchi & Wirz-Justice, 1994).


Furthermore, Krauchi and Wirz-Justice (1994) found that proximal body regions

such as the chest, thigh and forehead reflected the same relative temperature changes

to that of Tc, while more distal sites such as the hand and feet have an inverse

relationship with Tc rhythms. Particular interest has been given to these temperature

gradients between distal and proximal 𝑇sk sites as a predictor of sleep propensity

(Hasselberg et al., 2013; van Marken Lichtenbelt et al., 2006).

The endogenous changes in Tc throughout a given day, has led some

researchers to consider the optimal times for heat load management during exercise.

More specifically, it has been proposed that circadian rhythm prevents optimal

removal of heat loads at the skin during exercise in the early morning hours, and that

optimal heat loss occurs in the late afternoon (Aldemir et al., 2000; Arnett, 2002).

This is a result of Tc being lowest during the early morning just before awakening

which coincides with the body initiating a ‘heat gain’ phase (Krauchi & Wirz-Justice,

1994). The opposite can be said for late afternoon at the time of highest body

temperatures and the initiation of a more efficient ‘heat loss’ phase in the hours

leading up to sleep onset (Krauchi & Wirz-Justice, 1994).

Dominance, Asymmetry and Pathophysiology

In a novel investigation, Gross, Schuch, Huber, Scoggins, and Sullivan (1988)

observed both men and women found that dominance has no effect on contralateral

𝑇sk measurements at both the wrist and the knee. However, comparative studies have

used skin thermography to measure temperature differences between limbs, or

temperature thresholds at specific sites to aid in the diagnosis of illnesses and injury

(Table 2.2).


Table 2.2.

Examples of 𝑇sk changes used to aid in the diagnosis of illness and injury.

Author Pathology Identified Temperature

Wasner et al. (2002) CPRS I Asymmetries >2.1 °C

D. Armstrong, Lavery, Liswood, Todd, and Tredwell (1997) Diabetic Foot Ulcer Asymmetries >3.1 °C

Lavery et al. (2007) Diabetic Foot Ulcer Asymmetries >2.2 °C

Chiu et al. (2005) Fever Forehead >38 °C

Hausfater, Zhao, Defrenne, Bonnet, and Riou (2008) Fever Forehead >37.5 °C

Ring et al. (2008) Fever (Children) Forehead >36.9 °C

Hildebrandt, Raschner, and Ammer (2010) Overuse Knee Injury Asymmetries >1.4 °C

Ben-Eliyahu (1991) PFPS Asymmetries >1 °C

Davidson and Bass (1979) PFPS Asymmetries >0.5 °C

Mayr (1995) Post-operative knee surgery

Abnormal asymmetries >0.5 °C

Spalding et al. (2008) Rheumatoid Arthritis HDI >1.3 °C

Goodman, Heaslet, Pagliano, and Rubin (1985) Tibial Stress Fractures Asymmetries >0.5 °C

CPRS I: Chronic regional pain syndrome (nerve disorder); PFPS: Patellofemoral pain syndrome; HDI:

Heat distribution index.

In healthy subjects, normative healthy asymmetrical 𝑇sk differences between

sites have been reported to be as low as 0.25 °C (Uematsu, 1985a; Vardasca, 2008).

Comparative studies into bilateral differences within individuals have been

commonly used to detect the presence of a variety of pathologies (D. Armstrong et

al., 1997; Feldman & Nickoloff, 1984; Mayr, 1995; Uematsu, 1985b; Wasner et al.,

2002). These studies typically measure 𝑇sk with IC’s because of its superior data

collection and complete topography of the areas of interest (Costello, Stewart, Selfe,

Karki, & Donnelly, 2013). Overall, skin thermography is commonly used as a

diagnostic criteria in the identification and treatment of overuse and soft tissue

injuries (Ben-Eliyahu, 1991; Bouzida et al., 2009; Davidson & Bass, 1979; Goodman

et al., 1985; Hildebrandt et al., 2010; Mayr, 1995), influenza screening (Chiu et al.,

2005; Hausfater et al., 2008; Ring et al., 2008), malignant tumours (Arora et al.,

2008; Herman & Cetingul, 2011), autoimmune and nervous system diseases (D.


Armstrong et al., 1997; Lavery et al., 2007; Spalding et al., 2008; Wasner et al.,

2002).

Medications

Thermoregulatory responses, including 𝑇sk, have been used to evaluate the

effects of various medications such as analgesics, anti-inflammatories, vasoactives

and hormonal treatments (Ring, Engel, & Page-Thomas, 1984). In order to control

for potential thermoregulatory changes in participants on various medication, a

number of investigations have excluded participants currently taking medications

(Pascoe, Barberio, Elmer, & Wolfe, 2012; Ring & Ammer, 2000; Zaproudina,

Airaksinen, & Närhi, 2013; Zaproudina, Varmavuo, Airaksinen, & Närhi, 2008).

This logical approach is used despite no defined list of medications that influence

human thermoregulation or a standardised pre-examination screening of a patient’s

medication history. Currently, only one international standard (ASTM-E1965, 1998)

states that subjects should be excluded from measurement if an individual has used

“…medications known to affect body temperature (for example, antipyretics,

barbiturates, thyroid preparations, antipsychotics, etc.) within 3 h of the test, or

immunization within seven days of the test.” However, this recommendation is in

relation to tympanic Tc measurements taken with an infrared thermometer. Future

amendments to international standards should not overlook the potential for

erroneous 𝑇sk values, as a result of even commonly used medications such as

paracetamol, aspirin, ibuprofen and oral contraceptives.

2.7.2 Behavioural

Caffeine, Nicotine & Ethanol (Alcohol)

At present, the literature pertaining to the effect caffeine has on 𝑇sk is

contradictory – with increases (Koot & Deurenberg, 1995), decreases (Quinlan et al.,

2000) and no change reported (Daniels, Molé, Shaffrath, & Stebbins, 1998)

following consumption. Two studies have found attenuated 𝑇sk increases in

participants who have consumed hot coffee, compared to a hot water control group.

This response suggests caffeine has a vasocontrictive effect on peripheral blood

vessels (Quinlan, Lane, & Aspinall, 1997; Quinlan et al., 2000). Concomitantly, a

dose response was found between the attenuated 𝑇sk rises and greater caffeine

consumption (Quinlan et al., 2000). The authors attributed these increases in 𝑇sk to

caffeine’s pressor effects as a result of adenosine receptor antagonism. Because


caffeine molecules closely resemble the chemical adenosine, it is thought caffeine

blocks A1, A2A and A2B receptors in blood vessels, thereby acting as an antagonist

and decreasing cutaneous blood flow (Namdar et al., 2009). However, subsequent

research into the pressor mediator as a result of caffeine consumption found

increases were still present in decaffeinated coffee (Corti et al., 2002). This

conclusion suggests another factor within hot coffee, and not the caffeine itself,

initiates vasoconstriction and weakened 𝑇sk rises. The potential inconsistencies

between the aforementioned caffeine and 𝑇sk studies may be due to the administering

of the caffeine through hot beverages that alter vasomotor mechanisms (Koot &

Deurenberg, 1995; Quinlan et al., 2000) compared to an ingestible gel capsule

(Daniels et al., 1998).

Nicotine intake via cigarettes initiates subcutaneous vasoconstriction and

resultant 𝑇sk reductions in smokers by up to 7 °C (Sørensen et al., 2009; Weatherby,

1942; West & Russell, 1987). These acute changes in 𝑇sk can last up to 90-min after

smoking (Gershon-Cohen, Borden, & Hermel, 1969; Gershon-Cohen & Habennan,

1968). There is some inconsistency in the literature with one author reporting 𝑇sk

increases as a result of acute nicotine ingestion (Usuki, Kanekura, Aradono, &

Kanzaki, 1998). However, participants in this study chewed nicotine gum and did not

smoke a cigarette like in the previous investigations (Gershon-Cohen et al., 1969;

Gershon-Cohen & Habennan, 1968; Weatherby, 1942; West & Russell, 1987). The

chronic effects of smoking also alter thermoregulation through the narrowing of

blood vessels, potentially leading to health complications such as peripheral vascular

disease which reduces distal 𝑇sk (Huang et al., 2011).

Conversely, alcohol ingestion causes dilation of blood vessels thus increasing

𝑇sk (Ammer, Melnizky, & Rathkolb, 2003; Wolf, Tüzün, & Tüzün, 1999). Detailed

investigations regarding the influence of alcohol on 𝑇sk have shown a multifaceted

relationship between the two depending on other variables. For example, influences

are dependent on ethnicity (Harada, Agarwal, & Goedde, 1981), the increases in 𝑇sk

are amplified on an empty stomach (Mannara, Salvatori, & Pizzuti, 1993) or with

greater alcohol consumption (Finch, Copeland, Leahey, & Johnston, 1988); and the

increases are attenuated in ambient temperatures outside of 20 and 35 °C (Hughes,

Henry, & Daly, 1984; Risbo, Hagelsten, & Jessen, 1981) or if an individual

participates in habitual alcohol consumption (Mannara et al., 1993).


In summary, there is a wide range of conflicting evidence between the

direction and magnitude of temperature effects following the consumption of

caffeine, nicotine and alcohol. Researchers and clinicians should be aware that in any

case, influences are present after ingestion of these socially acceptable drugs and

should be controlled for when requiring accurate and reliable 𝑇sk measurements.

Food

There is a consensus within the literature that 𝑇sk increase as a result of food

intake, referred to as diet-induced thermogenesis (Dauncey, Haseler, Thomas, &

Parr, 1983; Shuran & Nelson, 1991; Westerterp-Plantenga, Wouters, & Ten Hoor,

1990). The thermic effect of feeding sees a rise in metabolic rate and oxygen

consumption causing a concomitant increase in body temperature (Rothwell & Stock,

1983). 𝑇sk increases tend to peak 90-min following eating and can take up to 3 hours

before a return to baseline levels depending on the skin site (Dauncey et al., 1983;

Westerterp-Plantenga et al., 1990).

Beverages

The influence of hydration status on Tc has been well defined (Sawka & Coyle,

1999; Sawka et al., 1998) with 𝑇sk largely overlooked. These studies note that during

endurance exercise dehydration blunts the thermoregulatory pathways that dissipate

heat loads. To counter these detrimental effects on performance, subsequent studies

have used ice slurry mixtures in an attempt to precool runners (Lee, Shirreffs, &

Maughan, 2008; Siegel et al., 2010; Siegel, Maté, Watson, Nosaka, & Laursen,

2012). In an investigation by Siegel et al. (2010) 𝑇�sk was reduced under resting

conditions following either cold water or ice slurry ingestion, with significant

differences between groups. Surprisingly, two other studies comparing the effect of

warm water and cold (Lee et al., 2008) or ice water (Siegel et al., 2012) during rest

and exercise and found no significant effect between water temperature and 𝑇�sk

during resting conditions. Unfortunately, neither study implemented a control group

that had no fluid, to see if the fluid itself and subsequent hydration status, regardless

of temperature, altered 𝑇�sk. Also, it may have been more beneficial to measure 𝑇sk

changes at individual sites. 𝑇�sk calculated from central and peripheral sites may have

prevented significant differences to be detected, as central 𝑇sk sites are less sensitive

to temperature changes than distal regions (Merla, Mattei, Di Donato, & Romani,

2010). Another study has reported the effect of sparkling water intake on 𝑇sk


(Ammer et al., 2003). The purpose of this study was to measure 𝑇sk in the hand,

knees and face during alcohol consumption. Surprisingly, the control group reported

significant 𝑇sk falls after consuming only sparkling water. Falls of up to 0.9 °C were

reported in the control group, though it was not clear if these changes could be a

result of the carbonic acid present in the sparkling water.

Exercise Performance and Acclimatisation

Training status and environmental acclimatisation influence the

thermoregulatory response and therefore 𝑇sk during exercise. For example the trained

have been shown to have higher resting and exercising 𝑇sk as a result of increase skin

blood flow compared to the untrained (Fritzsche & Coyle, 2000; Liu et al., 2004).

While the untrained have an impaired cooling capacity during exercise and a slower

𝑇sk recovery back to baseline (Merla et al., 2010). These same thermoregulatory

responses are present in populations that are acclimatised to the heat when compared

to the unacclimatised (Sawka, Wenger, & Pandolf, 2010).

Ambient temperature has also been shown to influence the work rate of

participants during self-paced exercise in the heat. (Tucker, Marle, Lambert, &

Noakes, 2006) examined the effect of exercise in the heat on pacing strategies on

eight cyclists and found that exercise in the heat (35 °C) saw significantly less

power-output and slower self-pacing when compared to normal (25 °C) or cool (15

°C) temperatures. As there were no significant differences in Tc or heat storage seen

between conditions, this response in altered self-paced exercise intensity was

attributed to the sympathetic feedback of thermoreceptors in located in the skin to

ensure thermal homeostasis is maintained.

2.8 SKIN TEMPERATURE MEASUREMENT TECHNIQUES

Means in which 𝑇sk can be acquired could be placed into two categories (1)

conductive and (2) infrared with each method having its own innate advantages and

limitations. The following sections will describe in detail the most commonly used

instruments for 𝑇sk assessment. A systematic review outlining the interchangeability

between conductive and infrared devices is presented in Chapter 3.


2.8.1 Conductive Devices

Conductive devices are based upon the transfer of heat energy into the device

through direct contact with the object of interest (discussed earlier in section

Thermodynamics). There are a wide variety of types, makes and models of

commercially available conductive devices. For the purpose of this review three of

the most popular types of devices will be introduced. Thermocouples (TC),

Thermistors (TM) and iButtons® (IB) are typical contact measures of 𝑇sk that have

been viewed as advantageous by clinicians due to the relatively low cost and the

associated ease of use (Tyler, 2011).

Thermocouples

TC function as a result of an interaction known as the Seebeck effect; where by

the temperature measured is proportional to the voltage between the probes of two

dissimilar metals when in the presence of a temperature gradient (Klopfenstein,

1994). In order to measure and record temperatures of interest, the TC’s must be

plugged into an associated data logger. Thermocouples are advantageous due to their

fast response, and accuracy over very wide temperature ranges (Yadav, Srivastava,

Singh, Kumar, & Yadav, 2012).

Thermistors

A TM is a wired sensor made from a semi-conductive metal that exhibits an

inverse relationship between temperature and the electrical resistance within the

device. Like TC’s, TM’s need a data logger to control thermocouple sampling rates

and store recorded data. TM’s have a high thermal sensitivity, fast response rate and

very accurate when measuring temperatures within the human physiological range

(≤100 °C; Klopfenstein, 1994).

iButtons®

An IB is a relatively new wireless device that is an autonomous, encapsulated

semiconductor sensor approximately 16 x 6mm2 in size. The IB’s major advantage

over the former conductive devices is wireless recording of temperatures. The IB has

been validated against more traditional TM (Harper Smith et al., 2010) and

thermocouples (van Marken Lichtenbelt et al., 2006), and has been shown to

successfully measure long-term 𝑇sk of extremities of both diabetic and healthy

subjects in free-living conditions (Rutkove et al., 2009). However, the major


drawback of the IB’s is that data must be viewed retrospectively once the device has

finished logging. Both the TM’s and the IB’s were chosen as the conductive devices

to be used as part of experimental testing during this project (details in Chapter 4,

Table 4.1 Device specifications).

2.8.2 Considerations When Using Conductive Devices

By design, conductive measurement devices must be in contact with the skin.

A wide variety of methodological factors have been shown to influence temperature

measurements in research settings. These include contact pressure, probe placement,

fixation method, sensor age and environmental conditions.

The application of adhesive tapes to 𝑇sk probes has the potential create a

microenvironment and disrupt heat transfer capacity through convection and

evaporation (Gonzalez & Sawka, 1988). Previous investigations have cited the lack

of consistency or reporting of attachment methods for conductive devices (Buono &

Ulrich, 1998; Tyler, 2011). Buono and Ulrich (1998) studied the influence of

‘covered’ and ‘uncovered’ TM measurements of 𝑇�sk during exercise in different

environmental conditions (thermoneutral, hot-humid and hot-dry). On three separate

occasions, subjects were required to walk for 30-min (6.4 km/h, 0% grade) while 𝑇�sk

was logged to the nearest 0.1 °C every 5-min with the TM’s taped to the skin and

held to the skin with an acrylic ring and elastic bands. Covered probes recorded

significantly higher temperatures under all conditions, ranging from 0.4 °C in hot-dry

to 1.3 °C in thermoneutral. Similar findings were noted by Tyler (2011) who

compared uncovered to covered TM’s of varying layers of tape in thermoneutral,

warm and hot conditions. Expectedly, temperature differences rose with additional

layers of tape which lead to a significant overestimation of 𝑇�sk between almost all

uncovered and layered methods. A more recent laboratory based study of 𝑇�sk devices

measuring a hot plate (36.5 °C) found temperature readings are significantly

influenced by the conductance of the tape, sensor shape and contact to the surface

and the ambient temperature (Psikuta, Niedermann, & Rossi, 2013).

Several layers of adhesive tapes are often applied to conductive devices to

ensure good contact and pressure, especially during exercise where movement and

sweat can lead to loss of contact (Buono et al., 2007). However, the surface contact

and pressure of the sensor itself can alter temperature measurements. Original


investigations by Stoll and Hardy (1950) found doubling contact pressure of

thermocouple probes could see temperature increases of up to 1.5 °C. Moreover, any

deviation in angular contact between the probe surface and the skin could lead to

erroneous readings drifting toward ambient temperature (Harper Smith et al., 2010).

Ambient temperatures have also been shown to influence the performance of

𝑇sk devices (Psikuta et al., 2013; van Marken Lichtenbelt et al., 2006). In a human

study of measurement differences between IB’s and TC’s in cold (15.5 °C; 8.6 %

RH) and hot (34.9 °C; 64 % RH) conditions, compared to the TC’s the IB’s

constantly underestimated 𝑇�sk in the cold (-0.24 °C) and constantly overestimated

𝑇�sk in the heat (0.88 °C; van Marken Lichtenbelt et al., 2006). These findings could

be intrinsically related to the composition and shape of the probes and their response

to thermal inertia of the ambient temperature in extreme conditions. Furthermore, the

impact of temperature changes to TC wires and the not sensing probe itself, have all

been reported (Jutte, Long, & Knight, 2010). In a water bath study of a number of

TC models, increased measurement artefacts were seen in TC probes after ice bags

were placed on top of the TC leads (Jutte et al., 2010).

Because of the dynamic nature of skin and the subcutaneous properties that

alter 𝑇sk (blood flow, fatness, metabolic rate), subjective probe placement within

regions of interest can lead to unreliable temperature measurements (Frim et al.,

1990; Pascoe et al., 2012). The placements of conductive devices within a specific

region of interest are described or depicted with each formula. Often, these

recommendations do not provide accurate or repeatable instructions for the

placement of probes based upon objective anatomical landmarks, but rather a vague

representation of placement, open to interpretation. Pascoe et al. (2012) used infrared

thermography to measure 𝑇sk variation across 13 commonly used 𝑇sk sites to

quantify the possible error associated with TM placement. The average temperature

site variation was 3.19 ± 0.93 °C. When the hottest and coolest measured

temperatures of the appropriate sites were transposed into the Burton (1934) 3-site

formula, the output 𝑇�sk had a range of 29.99 to 33.51 °C (difference = 3.52 °C). In

addition, it would be expected that this observed variation across the skin surface

would be magnified in colder ambient conditions where vasoconstriction occurs

(Frim et al., 1990).


2.8.3 Infrared Devices

Typically, infrared devices are used as a non-contact form of 𝑇sk measurement.

This review will focus on two types of thermographic instruments: infrared

thermometers (IT) and infrared thermal imaging cameras (IC). With the advent of

more technological advances and cheaper costs associated with infrared devices,

there has been a renewed interest in use of thermography in exercise science due to

superior data collection and non-contact nature (Costello et al., 2013).

All objects hotter than absolute zero (-273.15 °C), produce an electromagnetic wave

of radiation proportional to the electrical charge given off by vibrating atoms and

molecules that make up the object. Emissivity (ε) is the term used to describe the

amount of absolute radiation energy released from an objects surface relative to an

ideal black body (ε = 1.0; Blatteis et al., 2001). By knowing the emissivity

coefficient of an object’s surface it is possible to know the surface temperature of

that object (Modest, 2013). Human skin, irrespective of ethnicity, has an emissivity

resembling that of a perfect black body between 0.97-0.99 (Boylan, Martin, &

Gardner, 1992; Sanchez-Marin, Calixto-Carrera, & Villaseñor-Mora, 2009; Steketee,

1973; Togawa, 1989). The Stefan-Boltzmann law states that the power emitted per

unit area of the surfaces of a black body is directly proportional to the fourth power

of its absolute temperature:

P = εσAT4

where

P = power radiated (watts)

A = surface area (m2)

ε = emissivity (no units)

σ = Stefan-Boltzmann Constant (5.67x10-8 W m-2 K-4)

T= absolute temperature (Kelvin)

Figure 2.1 represents the electromagnetic spectrum which makes up

wavelengths outside of, and including, the visible light spectrum seen with the naked

human eye. Increased radiation energy is associated with shorter wavelengths and is

therefore more dangerous (e.g., gamma rays). Visible light makes up a small portion

of the electromagnetic spectrum and is between wavelengths of 380 to 780 nm.

Infrared 𝑇sk devices measure long-wave infrared radiation between wavelengths of

7500 and 14000 nm (7.5-14 µm). They detect the infrared radiation emitted from an


object within this range, and covert the input into an electrical signal which is

displayed in an output temperature or image (discussed further in following

sections).

Figure 2.1. The electromagnetic spectrum, depicting various properties including visible light and long-wave infrared radiation

Infrared Thermometers

Similar to the conductive devices mentioned previously (section 2.6.1

Conductive Devices), IT’s measure the average temperature over a small area, often

referred to as a ‘spot’ measurement. There are infrared thermometers that require

contact with the area of measurement (i.e., skin). However, the majority of infrared

devices are held off the skin which allows for temperature measurements without any

physical contact. An internal detector collects the infrared energy of an object with a

relatively simple ‘point and shoot’ design with an associated laser sighting for

aiming purposes. Most clinically used devices have manufacturer specified distances,

in which the device should be held from the skin to ensure accurate measurement

(e.g., 50 mm). Some other IT’s however, use a distance to spot ratio that allows for a

greater measurement area at longer distances, but at the cost of accuracy (Thomas,

2006). ASTM international standards (ASTM-E1965, 1998) state that prior to use an

IT “shall be stabilised at given conditions of ambient temperature and humidity for a

minimum of 30-min or longer if so specified by the manufacturer”. There are now

more advanced models with manual and automatic ambient re-calibration settings for

the use of IT’s in varying environmental conditions without the need for waiting for

stabilisation (e.g., testing air conditioning then moving outside).


Infrared Cameras

IC’s are characterised into two categories: cooled and uncooled. Cooled

cameras require liquid nitrogen cooling and produce more accurate and sensitive

measurements (Qi & Diakides, 2007). These cameras cost well outside the budgets

of typical research laboratories and are used almost exclusively in military

engineering and commercial industries. Uncooled cameras used predominantly in

medical settings are compact, portable and markedly cheaper than their cooled

counterparts (Diakides, 1997); but the initial and associated costs make them a

relativity expensive 𝑇sk measurement device compared to cheaper conductive and IT

options. The use of an uncooled IC typically requires the camera, a tripod and a

connected computer for image display and image processing via dedicated software.

The continual development of infrared thermography has seen it become widely

adopted as a diagnostic tool among the medical community with recent medical

applications including mass fever screening (Ring & Ammer, 2012); breast cancer

monitoring and detection (E. Ng, 2009); observation of osteoarthritic progression and

identification of overuse injury such as ‘tennis elbow’ (Hildebrandt et al., 2010).

Modern uncooled IC’s exhibit an erroneous thermal drift when turned on or

moved (Ring et al., 2007) and therefore, much like IT’s, require time to stabilise to

the surrounding ambient conditions for accurate measurement (normally 30-60 min;

Grgić & Pušnik, 2011). An uncooled IC and a clinical standard used IT were used

for all testing as part of this project (details in Chapter 4, Table 4.1 Device

specifications).

2.8.4 Considerations When Using Infrared Devices

The identification and selection of regions of interest for studies implementing

IC’s are poorly standardised, leaving authors to select their preferred measurement

area within a previous defined region of interest or create their own. For example, as

of 2009 up to 20 different angles, field of view and image analysis were reported to

measure hand temperatures (Ammer, 2009). This variation has been shown to lead to

significant 𝑇sk differences between methods of image analysis (Ludwig, Formenti,

Gargano, & Alberti, 2014), increase unreliable measurements within and between

both subjects and operators (Ring & Ammer, 2000; Zaproudina et al., 2008), as well

as confining the accurate comparison of thermography studies. A number of authors

have tried to implement their own universal region of interest standardisation with


limited adoption from the greater scientific community (Ammer, 2008; Fernández-

Cuevas et al., 2012). A consensus for the universal standardisation of regions of

interest, using more objective means, such as inert markers attached to anatomical

landmarks, need to be established to help improve 𝑇sk measurements derived from

thermal images.

IC set up including measurement position, distance and environmental

conditions can influence the quality of data collected. Camera distance should vary

upon the size of the measurement area and the optical specifications of the camera.

To maximise data collection by increasing functional pixels, the IC should be placed

as close as possible so the measurement surface fills the entire field of view while

maintaining focus (Ammer, 2003). For the most accurate temperature measurements

infrared devices are required to be positioned perpendicular to the measurement

surface of interest. Any deviation away from 0° causes the device to read thermal

radiation from the surroundings being reflected from the skin (Watmough, Fowler, &

Oliver, 1970). Ammer (2003) reported deviations between 0 and 30° alter the

emissivity values of the skin and begin to limit the radiative energy measured by the

device, while deviations of 30 and 60° produce substantially erroneous data (±1 °C).

In order to minimise any environmental influences, data collection should be

conducted in a stable controlled setting of 18 to 25 °C (Ring & Ammer, 2000), free

of external radiation sources (i.e., sun) and the use of a uniform. Matte background

behind the participant is recommended to avoid any reflective radiation.

Finally, the presences of ointments, cosmetics, liquids and hair on the

measurement area can cause inaccurate 𝑇sk readings (Bernard, Staffa, Mornstein, &

Bourek, 2013; Korichi et al., 2006; Steketee, 1976). The topical application of water,

creams and gels has been shown to produce reductions in 𝑇sk measurements through

infrared means by up to 4.86 °C (Bernard et al., 2013). Further to this, human hair is

an avascular structure with a lower emissivity, thermal conductivity and heat

capacity than human skin and has been shown to produce relativity lower

temperatures than hair-free skin (Togawa & Saito, 1994). Few authors have

controlled for hair along the skin during infrared imaging, advising that any relevant

body hair is removed in the days preceding testing to avoid micro-trauma from

shaving and consequently artificially raising 𝑇sk (Merla et al., 2010). Overall, each of

these substances mentioned creates a physical barrier, with unique emissive and


thermal properties, between the skin surface and the infrared detector. Therefore, it

should be recommended that before infrared 𝑇sk measurements, participants should

have any relevant regions of interest cleaned with alcohol (allowed to dry) and be

free of hair.

2.9 DEFINING INTERCHANGEABLILTY

A correlation coefficient is a measure of the strength of linear dependence

between two variables and does not measure the strength of the agreement. For

example, comparing 𝑇sk values derived from a TM and IC would achieve a perfect

correlation if all recorded data points fell along any straight line (Bland & Altman,

1995). However, a perfect agreement between the two methods would require the

data to fall along the same line as one another. In order to ensure that two separate

measurements techniques are classified as interchangeable (i.e. in agreement), more

robust techniques such as the comparison of mean differences are needed (Bland &

Altman, 1986). Current practice suggests that for any two conductive and infrared

𝑇sk devices to be considered interchangeable, mean temperature differences should

not exceed the proposed clinical significant difference of 0.5 °C (Joly & Weil, 1969;

Kelechi et al., 2011; Kelechi et al., 2006; Selfe et al., 2008). Statistical significant

differences between means will also be determined throughout the subsequent

original investigations. Therefore for the purpose of this thesis, devices will only be

considered interchangeable if they do not exceed clinical (mean differences >0.5 °C)

and statistical (P < 0.05) significance.

2.10 CONCLUSION

This literature review aimed to explain the mechanisms by which the human

body thermoregulates and more specifically how the skin facilitates heat loss or gain.

Furthermore, it was explained how 𝑇sk is influenced by a variety of intrinsic and

extrinsic factors and the limitations of each of the devices typically used to measure

the temperature of human skin. The following section (Chapter 3) narrows the focus,

by systematically reviewing the current literature that has compared infrared and

conductive devices to determine if there is a consistent bias between the two

modalities.

Chapter 3: Are conductive and infrared devices for measuring skin temperature interchangeable? A Systematic Review 39

Chapter 3: Are conductive and infrared devices for measuring skin temperature interchangeable? A Systematic Review

3.1 INTRODUCTION

Skin temperature (𝑇sk) is an important physiological measure that can reflect

the presence of illness and injury as well provide insight into the localised

interactions between the body and the environment. 𝑇sk has a wide range of

applications that consist of, but are not limited to, the assessment of; overuse injuries

(Hildebrandt et al., 2010; Meknas, Odden-Miland, Mercer, Castillejo, & Johansen,

2008), physiological strain (Cuddy et al., 2013), hypoxia (Cipriano & Goldman,

1975), exercise performance,(Davis & Bishop, 2013; Kenefick, Cheuvront, Palombo,

Ely, & Sawka, 2010; Levels, de Koning, Foster, & Daanen, 2012; Price, 2006; Ross,

Abbiss, Laursen, Martin, & Burke, 2013; Schlader, Simmons, Stannard, & Mundel,

2011; Wegmann et al., 2012), pacing strategies (Tucker, 2009), cold exposure

(Bleakley et al., 2012; Costello, Algar, & Donnelly, 2012; Kennet, Hardaker, Hobbs,

& Selfe, 2007; Selfe, Hardaker, Thewlis, & Karki, 2006), fever screening (Bitar et

al., 2009; Chan et al., 2004; Chiu et al., 2005; Nguyen et al., 2010), thermal comfort

and sensation (Wang et al., 2007), circadian rhythm (Hasselberg et al., 2013; van

Marken Lichtenbelt et al., 2006; Yosipovitch et al., 1998), complex region pain

syndrome (Koban, Leis, Schultze-Mosgau, & Birklein, 2003; Wasner et al., 2002)

and when coupled with core body temperature can determine mean body temperature

(Colin et al., 1971). Consequently, the assessment of 𝑇sk is extremely important in

sports medicine, exercise science, occupational, clinical and public health settings.

Thermoreceptors located within the hypothalamus, spinal cord, skin and some

abdominal organs monitor temperature changes, and work via negative feedback to

initiate autonomic mechanisms to either conserve (via shivering and

vasoconstriction) or lose (via sweating and vasodilation) body heat (Casa et al.,

2007). The human body controls core body temperature within a tight band typically

between 36 and 38 °C despite varying ambient temperatures. When core temperature

rises, for example during exercise, the anterior hypothalamus detects the temperature

40 Chapter 3: Are conductive and infrared devices for measuring skin temperature interchangeable? A Systematic Review

of blood perfusing it and once temperatures exceed an internal set point, vasodilation

of peripheral blood vessels and evaporation of sweat generated along the skin surface

facilitates heat loss (Charkoudian, 2003). As a result, 𝑇sk is influenced by a number

of factors including superficial blood flow, heat conduction from deeper tissues

(including muscle) and heat loss along the skin surface (Sawka, Leon, Montain, &

Sonna, 2011). The skin is also the site of reciprocal heat transfer between the human

body and the external environment. The extent to which heat transfer occurs is

largely dependent on the environmental conditions, such as ambient temperature,

water vapour and the thermal properties of human skin (Prek & Butala, 2010). For

example, radiation energy, the loss or gain of heat from infrared rays, imposed upon

the skin through the surrounding environment, increases thermal loads as a function

of the skin absorption characteristics and emissive properties (Cohen, 1977).

The most common methods of assessing 𝑇sk are derived from conductive and

infrared devices (Table 3.1). These techniques measure temperature by applying

different scientific principles of thermal heat transfer. Conductive methods are based

upon thermal conduction as a result of physical contact between the object of interest

and the measurement device (Boetcher, Sparrowb, & Dugay, 2009). To assess 𝑇sk,

this contact is typically made by affixing the device to the skin via medical adhesive

tape. Infrared devices detect thermal radiation in the infrared spectrum that is emitted

from the skin (Anbar, 2002). While most infrared devices are non-contact (e.g.

thermal imaging), it is necessary for some handheld infrared thermometers to be

placed against the skin. Popular conductive devices include thermistors (TM),

thermocouples (TC) and iButtons®; while popular infrared devices include thermal

imaging cameras (IC) and handheld infrared thermometers (IT). All devices vary in

cost (Foto, Brasseaux, & Birke, 2007; Harper Smith et al., 2010), error (Bernard et

al., 2013; Boetcher et al., 2009; Harper Smith et al., 2010; Psikuta et al., 2013),

response time (Foto et al., 2007; Harper Smith et al., 2010; van Marken Lichtenbelt

et al., 2006) and reliability (Hasselberg et al., 2013; Long, Jutte, & Knight, 2010;

Versey, Gore, Halson, Plowman, & Dawson, 2011; Zaproudina et al., 2008).


Table 3.1.

Description of devices

Device Description C

ondu

ctiv

e D

evic

es

Thermocouple

A surface temperature probe based upon the Seebeck effect, where by temperature

measured is proportional to the voltage between two dissimilar metals in the presence of a

temperature gradient.

Thermistor A surface temperature probe with an internal temperature sensitive resistor that measures

temperature by using a non-linear relationship between resistance and temperature; i.e., as

the temperature of a thermistor increases, the resistance within the thermistor decreases.

Both Thermistors and Thermocouples are typically connected to an associated data

logger.

iButton® A small (~16 x 6mm2), self-enclosed, self-sufficient, programmable, wireless device that

stores temperature values in an internal memory for retrospective extraction.

Infr

ared

Dev

ices

Thermal

Imaging

Camera

Within a video camera a radiometer detects infrared energy as a function of temperature

and converts the electronic video signal into an image displayed on a connected computer.

Temperatures are represented in grayscale or various colours with a single pixel

representing one temperature datapoint. Users have the ability to select specific regions of

interest from the image with post-analysis software.

Handheld

Infrared

Thermometer

Typically a stand-alone device that gives a single temperature reading by assessing

infrared energy at a localised ‘spot’ measurement. The device optics and the distance from

the object of interest determine the size of the spot measurement. However, some

thermometers are designed to be in contact with the object of interest. Tympanic infrared

thermometers are also used clinically to assess 𝑇sk.

Extensive investigations regarding the validity of the method of core

temperature measurement have taken place, with rectal thermometers widely

regarded as the gold standard of core body temperature measurement (Binkley et al.,

2002; Casa et al., 2007; Ganio, Brown, Casa, Becker, & Yeargin, 2009; Moran,

2002). Conversely, 𝑇sk has no recognised criterion (Harper Smith et al., 2010).

Despite the obvious differences in measurement techniques, and indeed the heat

transfer principles of the devices used to assess 𝑇sk, few authors have considered the

potential difference between conductive and infrared technologies. Furthermore, over

the past decade considerable advances in the technology leading to greater accuracy,

functionality and affordability have seen infrared devices, particularly thermal

imaging, become more widely adopted (Costello, McInerney, et al., 2012; Costello et

al., 2013). However, a brevity of research exists within the literature comparing


measurement differences between conductive and infrared techniques (Costello,

McInerney, et al., 2012).

Despite the differences in scientific principles underpinning each method,

many scientists and clinicians assume interchangeability between devices under all

circumstances. Current practice suggests that for any other device to be considered

interchangeable temperature differences should not exceed the proposed clinical

significant difference of 0.5 °C (Joly & Weil, 1969; Kelechi et al., 2011; Kelechi et

al., 2006; Selfe et al., 2008). Importantly, these relatively low thresholds illustrate

that only small variations between devices are needed to produce erroneous data that

significantly influences the conclusions drawn by researchers and clinicians. Due to

the significant role of 𝑇sk in thermoregulation and pathophysiology, a systematic

review examining the validity of using conductive and infrared devices

interchangeably is required. Therefore, our aim was to review the irregularities

between conductive and infrared means of assessing 𝑇sk which are commonly

employed in exercise science and sports medicine.

3.2 METHOD

3.2.1 Search Strategy

Searches were performed in the Cochrane Central Register of Controlled

Trials, MEDLINE, SportsDiscus and CINHAL. A total of 19 MeSH or keywords and

their combinations were searched using Boolean operators (skin temperature, tissue

temperature, surface temperature, valid*, reliab*, repeatability, interchange*,

compar*, contrast, differences, contact, non-contact, ibutton*, thermograph*,

thermistors, thermocouples, thermometer, infrared camera, thermal imag*). Each

database was searched from January 1998 to February 2014. Potentially relevant

articles were also obtained by physically searching the bibliographies of included

studies to identify any study that may have escaped the original search. A total of

6036 articles were identified (Figure 3.1).

Chapter 3: Are conductive and infrared devices for measuring skin temperature interchangeable?A Systematic Review 43

Figure 3.1. PRISMA flow chart describing the selection and exclusion of articles.

3.2.2 Inclusion Criteria

Due to the advent of digital technology and substantial technological advances

in the last 15 years, original papers published since 1998 were preferentially

considered. In addition, studies meeting the following criteria were included in the

review: 1) the literature was written in English, 2) participants were human (in vivo),

3) skin surface temperature was assessed at the same site, 4) with at least two

commercially available devices employed – one conductive and one infrared – and 5)

had 𝑇sk data reported in the study.

3.2.3 Data Extraction and Management

Data were extracted independently by two review authors using a customised

form. This was used to extract relevant data on methodological design, participants,

comparisons of devices (conductive and infrared) and techniques used, region of

interest and environmental conditions. Any disagreement was resolved by consensus,


or third-party adjudication. Although measurement devices may have been reported

significantly different (statistically); if a study reported mean differences within 0.5

°C, for the purpose of this review they were classified as interchangeable. Where

numerical values were not reported, data was manually extracted from any relevant

graphs or figures. There was no blinding to study author, institution or journal at this

stage.


Table 3.2. Details of articles included in the systematic review

Authors Techniques Sample Size (M:F);

Age (y)^ Sites Methods and Conditions Findings

Conductive Infrared

Buono et al. (2007)

(observational)

TMA ITB 6 (0:6) healthy;

25 ± 3

𝑇�sk reported – 3 site formula[52]

(Chest, Forearm

and Calf)

1. Seated rest

Acclimatisation = 10-min

Troom = 15, 25 & 35 °C

(40 % RH)

Other = wind speed (ν <1.0 m·s-1) 2. Treadmill

(4.82 km·h-1, 0% Grade)

Duration = 15-min

Troom = 15, 25 & 35 °C

(40 % RH)

1. Rest#

15°C: IT < TM (0.2 °C)

25°C: IT > TM (0.4 °C)

35°C: IT > TM (0.9 °C)

2. Exercise#

15°C: IT < TM (0. 1°C)

25°C: IT < TM (0.6 °C)

35°C: IT > TM (0.1 °C)

Burnham et al. (2006) (observational)

TMC 1. ITD

2. ITE

17 (12:5) healthy;

29.5 ± 8.5

Shoulder

Forearm

Hand

Thigh

Shin

Foot

Mode = NR

Acclimatisation = NR

Troom = NR

1. ITD vs. TM

Shoulder: IT < TM (0.7 °C)

Forearm: IT < TM (0.5 °C)

Hand: IT < TM (0.5 °C)

Thigh: IT < TM (0.5 °C)

Shin: IT < TM (0.3 °C)

Foot: IT < TM (0.4 °C)

All Sites: IT < TM (0.5 °C)

2. ITE vs. TM

Shoulder: IT < TM (0.2 °C)

Forearm: IT < TM (0.1 °C)

Hand: IT < TM (0.2 °C)

Thigh: IT < TM (0.3 °C)

Shin: IT < TM (0.1 °C)

Foot: IT < TM (0.2 °C)

All Sites: IT < TM (0.2 °C)

Fernandes et al. (2014) (randomised crossover)

TCF ICG 12 (12:0) healthy;

22.4 ± 3.3 𝑇�sk reported –

8 site formula[55]

(Forehead, Chest,

Abdomen, Scapula,

Arm, Forearm,

Thigh and Calf)

1. Standing rest


2. Treadmill (60 %VO2max)

Duration = 60-min

3. Standing recovery

Duration = 60-min

Troom TC = 24.9 ± 0.6 °C

(62.3 ± 5.7 % RH)

Troom IC = 24.8 ± 0.4 °C

(61.9 ± 5.4 % RH)

1. Rest

IC > TC (0.75 °C)

2. Exercise

IC < TC (1.22 °C)

3. Recovery

IC > TC (1.16 °C)


Study (Type)

Techniques Sample Size (M:F); Age (y)#

Sites Methods Findings Conductive Infrared

Kelechi et al. (2011) (observational)

TMH ITI 17 (12:5) healthy;

29.5 ± 8.5

Medial Aspect of

Right Lower Leg

Lying rest


Troom = 23 ± 1.3 °C (% RH = NR)

Other =

1. post 10-min acclimatisation

2. further 10-min

3. after 10-min cold application

1. IT > TM (0.2 °C)*

2. IT > TM (0.1 °C)*

3. IT > TM (0.3 °C)*

Kelechi et al. (2006) (observational)

TMJ ITK 55 (26:29);

69.8 ±11.5

Medial Aspect of Lower Legs

Seated rest

Acclimatisation = ~30-min

Troom = 22 °C (% RH = NR)

Other = Assessed on 3 days (7 days apart)

1. Left Leg: IT < TM (0.13 °C)

2. Left Leg: IT < TM (0.16 °C)

3. Left Leg: IT = TM (0.00 °C)

Right Leg: IT < TM (0.10 °C)



Korukçu and Kilic (2009) (observational)

TCL ICM 3 (3:0) healthy;

25 ± 2.6

Face

Forearm

Finger

1. Passive heating

2. Passive cooling

Duration = 30-min (each)

Troom = NR

1. IC < TC (°C = NR)

2. IC > TC during cooling (°C = NR)

Maximum differences between IC and TC <2°C at any instance during heating or cooling period.

Matsukawa et al. (2000) (observational)

TCN ITO 10 (10:0) healthy;

30 ± 5

Forearm

Finger

Recovery from localised passive heating

Duration = 30-min

Troom = 22 – 23 °C (% RH = NR)

Forearm: IT < TC (0.5 °C)

Finger: IT < TC (0.5 °C)

Roy et al. (2006) (observational)

TMP ITQ 17 (6:11) healthy;

25.6 ± 5.4

Paraspinal

(C4 & L4)

Prone rest

Acclimatisation = 20 – 30-min

Troom = 20.5 - 23.3 °C (% RH = NR)

Other = Repeated on 4 other days

Overall:

Left C4: IT > TM (1.23 °C)

Left L4: IT > TM (1.56 °C)

Right C4: IT > TM (1.67 °C)

Right L4: IT > TM (1.62 °C)

Ruopsa et al. (2009)

(observational)

TCR ITS 38 (NR); NR Middle finger of

both hands

Mode = NR

Acclimatisation = NR

Troom = NR

At 𝑇sk between 31.5 – 35 °C:

IT < TC (0.06 °C)

At 𝑇sk between 21.5 - 31.4 °C:

IT < TC (1.01 °C)


Authors Techniques Sample Size (M:F);

Age (y)# Sites Methods and Conditions Findings

Conductive Infrared

van den Heuvel et al (2003)

(observational)

TMT ICU 4 (1:3) healthy;

26.8 ± 2.2

Fingertips

Palms

Forearms

Feet

Seated or supine rest


Troom = 25 ± 1 oC (% RH = NR)

On average across all sites, IC < TM (2.32 °C)

TM = Thermistors, TC = Thermocouples, IT = Handheld Infrared Thermometer, IC = Infrared Camera, M = Male, F = Female, 𝑻𝐬𝐤 = Skin Temperature, 𝑻�𝐬𝐤 = Mean Skin Temperature, Troom = Room Temperature, RH =

Relative Humidity, NR = Not Reported. ^ = Data for ages are presented in years (means ± SD) or not reported where stated. * = Received through first author correspondence. # = Derived from graphs presented in

publication.

A = Series 400 (YSI, Ohio, USA), B = (Extech Instruments, Massachusetts, USA); C = 113050 (Rochester Inc., New York, USA), D = 3000A (Genius, Sherwood IMS, California, USA), E = DT-1001 (Exergen,

Massachusetts, USA); F = S-09K thermocouples (Instrutherm, São Paulo, Brazil), G = ThermaCam T420 (FLIR Systems, Oregon, USA); H = PeriFlux 5020 Temperature Unit (Perimed, Stockholm, Sweden), I =

TempTouch (Diabetica Solutions, Texas, USA); J = PeriFlux 5020 Temperature Unit (Perimed, Stockholm, Sweden), K = ThermoTrace Model 15012 (DeltaTrak, California, USA); L = T-type thermocouples

(Physitetemp, New Jersey, USA), M = ThermaCam SC640 (FLIR Systems, Oregon, USA); N = TC (Mon-a-Therm, Mallinckrodt Anaesthesiology Products, St. Louis, Missouri, USA), O = Tympanic IT with attached 𝑇sk

probe (Genius, Sherwood IMS, California, USA); P = Model Et-016-STP/OWL-ET-016-STP (General Electric via Digi-Key, Minnesota, USA), Q = Subluxation Station Insight 7000 (EMG Consultant Inc., New Jersey,

USA); R = (Datex-Engstom, Helsinki, Finaland), S = PhotoTemp MX6 (Raytek, Califonia, USA); T = Steri-Probe type 499B (Cincinnati Sub Zero, Ohio, USA), U = MMS Med2000 camera (Meditherm, Queensland,

Australia).


3.3 RESULTS

3.3.1 Included studies

Ten articles met the inclusion criteria for this review, the characteristics of

which are summarised in Table 3.2 (Buono et al., 2007; Burnham et al., 2006;

Fernandes et al., 2014; Kelechi et al., 2011; Kelechi et al., 2006; Korukçu & Kilic,

2009; Matsukawa et al., 2000; Roy et al., 2006b; Ruopsa et al., 2009; van den Heuvel

et al., 2003). One article was excluded from the current review as the data was

previously reported in another publication (Roy, Boucher, & Comtois, 2006a). This

was confirmed following personal communication with the authors. Of the ten

studies the total sample comprised of 179 participants (82 male, 59 female); the sex

of 38 participants was unknown (Ruopsa et al., 2009). The mean sample of the

pooled studies was 18, with the largest study including a total of 55 participants

(Kelechi et al., 2006). Participant mean ages ranged from 22 (Fernandes et al., 2014)

to 70 years (Kelechi et al., 2006); one study failed to report the age of the

participants (Ruopsa et al., 2009). Nine of the ten investigations used an

observational study design (Buono et al., 2007; Burnham et al., 2006; Kelechi et al.,

2011; Kelechi et al., 2006; Korukçu & Kilic, 2009; Matsukawa et al., 2000; Roy et

al., 2006b; Ruopsa et al., 2009; van den Heuvel et al., 2003), with one randomised

crossover trial (Fernandes et al., 2014). In relation to statistical power, only one study

(Kelechi et al., 2006) incorporated a prospective power analysis to identify the

sample size necessary to achieve statistical significance.

3.3.2 Detail of Comparisons

Of the ten included studies comparing conductive and infrared methods of

assessing 𝑇sk, four types of devices were used; thermistors (Buono et al., 2007;

Burnham et al., 2006; Kelechi et al., 2011; Kelechi et al., 2006; Roy et al., 2006b;

van den Heuvel et al., 2003), thermocouples (Fernandes et al., 2014; Korukçu &

Kilic, 2009; Matsukawa et al., 2000; Ruopsa et al., 2009), infrared cameras

(Fernandes et al., 2014; Korukçu & Kilic, 2009; van den Heuvel et al., 2003) and

handheld infrared thermometers (Buono et al., 2007; Burnham et al., 2006; Kelechi

et al., 2011; Kelechi et al., 2006; Matsukawa et al., 2000; Roy et al., 2006b; Ruopsa

et al., 2009). Within the handheld infrared thermometers, both contact (Burnham et

al., 2006; Kelechi et al., 2011; Roy et al., 2006b) and non-contact (Buono et al.,

2007; Kelechi et al., 2006; Matsukawa et al., 2000) models were utilised. In addition,


two studies (Burnham et al., 2006; Matsukawa et al., 2000) used a tympanic infrared

thermometer to measure 𝑇sk and a single study (Burnham et al., 2006) tested three

devices, by comparing two different handheld infrared thermometers to a conductive

device. Information pertaining to the individual device model and manufacturer is

reported in Table 3.1.

Local 𝑇sk was measured at the face (Korukçu & Kilic, 2009), shoulder

(Burnham et al., 2006), paraspinal regions (Roy et al., 2006b), forearm (Burnham et

al., 2006; Matsukawa et al., 2000; van den Heuvel et al., 2003), hand and fingers

(Burnham et al., 2006; Matsukawa et al., 2000; Ruopsa et al., 2009; van den Heuvel

et al., 2003), thigh (Burnham et al., 2006), lower leg (Burnham et al., 2006; Kelechi

et al., 2011; Kelechi et al., 2006) and foot (Burnham et al., 2006; van den Heuvel et

al., 2003). Two studies (Buono et al., 2007; Fernandes et al., 2014) compared mean

skin temperature (𝑇�sk) values between devices using the 3-site (chest, forearm and

calf) equation developed by Burton (1934); and the 8-site (forehead, chest, abdomen,

scapula, arm, forearm, thigh and calf) developed by Nadel et al. (1973).

Measurements were taken with devices during rest (Buono et al., 2007;

Fernandes et al., 2014; Kelechi et al., 2011; Kelechi et al., 2006; Roy et al., 2006b;

van den Heuvel et al., 2003), exercise (Buono et al., 2007; Fernandes et al., 2014),

passive heating (Korukçu & Kilic, 2009; Matsukawa et al., 2000) and passive

cooling (Kelechi et al., 2011; Korukçu & Kilic, 2009). It was not clear what

environmental conditions were employed in two studies (Burnham et al., 2006;

Ruopsa et al., 2009). Reported ambient temperatures ranged from 15 to 35 °C

(Buono et al., 2007), with three studies failing to describe ambient conditions in

which testing took place (Burnham et al., 2006; Korukçu & Kilic, 2009; Ruopsa et

al., 2009) and only two studies reported an average relative humidity (ranging from

40 to 62%; Buono et al., 2007; Fernandes et al., 2014).

3.3.3 Risk of bias

In order to assess the strength of the current body of evidence a systematic

evaluation of the risk of bias was undertaken as part of this review. This was

conducted under four applicable measurements, random sequence generation,

allocation concealment, blinding and incomplete outcome data (Figure 3.2).


Figure 3.2. Included Studies: risk of bias summary.

3.3.4 Study heterogeneity

Meta-analyses were not undertaken because of clinical heterogeneity. This

related to clinical diversity in terms of a number of key study characteristics:

participants, environmental conditions, exercise intervention, devices and location of

𝑇sk assessment.

3.3.5 Cold Environment and Cryotherapy

Three studies (Buono et al., 2007; Kelechi et al., 2006; Korukçu & Kilic, 2009)

compared devices under cold environmental conditions. More specifically, 10 °C

ambient temperatures (Buono et al., 2007), passive air cooling (Korukçu & Kilic,

2009) and following 10-min of ice pack application (Kelechi et al., 2011). Buono et

al. (2007) found no statistical or clinical differences between a TM and an IT when

determining 𝑇�sk during passive rest or exercise in cold ambient conditions, with

mean differences (MD) of 0.2 °C (95% CI -2.63 to 3.03 °C) and 0.1 °C (95% CI -

2.97 to 3.17 °C) respectively.

Using a glycerine-based gel wrap to cool the measurement site, Kelechi et al.

(2006) reported 12/17 (71%) of measurements taken between a TM and IT were

outside the clinically important limits (>0.5 °C) with a MD of 0.3 °C. However, this

study (Kelechi et al., 2006) did not control the application of the cold gel which was

placed directly over the TM probe at different pressures and locations over the

measurement site. Consequently, these findings should be treated with caution.

Korukçu and Kilic (2009) used a TC to validate the use of an IC during passive

cooling in an automobile, recording every 10-seconds for 30-min. On average the TC

recorded greater 𝑇sk values than that of the IC, but unfortunately the mean

Chapter 3: Are conductive and infrared devices for measuring skin temperature interchangeable?A Systematic Review 51

differences between the devices were not reported. However, it was noted that

differences did not exceed 2 °C at any time.

3.3.6 Thermoneutral Environment

Six studies (Buono et al., 2007; Fernandes et al., 2014; Kelechi et al., 2011;

Kelechi et al., 2006; Roy et al., 2006b; van den Heuvel et al., 2003) reported that

testing was conducted in a thermoneutral environment. Two other studies (Burnham

et al., 2006; Ruopsa et al., 2009) failed to report the ambient conditions or the

positioning of the participants (i.e., seated rest, prone) but it is assumed that these

studies took place in stable thermoneutral environments with the participants

passively resting. The mean differences between conductive and infrared devices for

all thermoneutral studies are presented in Figure 3.3. Across the eight thermoneutral

studies, three found conductive instruments measured elevated 𝑇sk values compared

with their infrared counterparts; MD 0.5 °C (95% CI -0.51 to 1.58 °C; Burnham et

al., 2006), MD 1.01 °C (95% CI 0.62 to 1.40 °C; Ruopsa et al., 2009), MD 2.32 °C

(95% CI 3.39 to 1.25 °C; van den Heuvel et al., 2003). The remaining five studies

(Buono et al., 2007; Fernandes et al., 2014; Kelechi et al., 2011; Kelechi et al., 2006;

Roy et al., 2006b), reported lower conductive device temperatures: MD of 1.24 to

1.61 °C depending on site (Roy et al., 2006b); similar device temperatures: MD 0.1

to 0.2 °C (Kelechi et al., 2011) and 0.08 to 0.21 °C (Kelechi et al., 2006) depending

on time; and mixed results depending on condition, i.e., rest: MD 0.4 °C (95% CI -

3.06 to 2.26 °C; Buono et al., 2007), MD 0.75 °C (-0.03 to 1.52 °C; Fernandes et

al., 2014); exercise: MD -0.6 °C (95% CI 0.88 to -2.08 °C; Buono et al., 2007), MD

-1.22 °C (-2.61 to 0.16 °C; Fernandes et al., 2014); recovery: MD 1.16 °C (-0.15 to

2.48 °C; Fernandes et al., 2014)(All conditions depicted in Figure 3.3).

3.3.7 Hot Environment

Matsukawa et al. (2000) observed MD of 0.5 °C (95% C1 -0.12 to 1.12 °C) in

the forearm and fingers, measured by a TC and a tympanic IT attached with a

commercially available 𝑇sk probe following 30-min of passive warming. When

comparing an IT and a TM during rest and exercise Buono et al. (2007) found MDs

in 𝑇�sk of 0.9 °C (95% CI -2.12 to 0.32 °C) and 0.1 °C (95% CI -0.61, 0.41 °C)

respectively. Analogous to the passive cooling protocol, Korukçu and Kilic (2009)

stated differences for any one measurement point did not exceed 2 °C during passive

heating. However, as stated previously insufficient data was published in order to


report mean differences/effect sizes between the devices and therefore this study was

excluded from Figure 3.3.

Figure 3.3. Forest plot, skin temperature comparison for 8 of the 9 included studies: Conductive vs. Infrared, outcome: mean skin temperature difference. # Based upon

values derived from publication; * data received from correspondence with first author; C4 = Cervical vertebrae 4; L4 = Lumbar vertebrae 4; T1 = Time 1; ITD =

3000A (Genius, Sherwood IMS, California, USA); ITE = DT-1001 (Exergen, Massachusetts, USA).


3.4 DISCUSSION

3.4.1 Evaluation of Methodological Quality

There were large limitations within the current evidence base. Sample size was

consistently small and the subsequent power of individual trials was questionable.

The number of participants in each of the included studies was generally small, with

over 75% of the included studies using a sample smaller than 18 participants. The

majority of studies failed to report a priori power analysis, potentially preventing

robust conclusions to be drawn from the evidence. There was also a consistently high

risk of bias across the studies, in terms of random sequence generation, allocation

concealment, blinding and incomplete outcome data (Figure 3.2). We acknowledge

the practical difficulties of blinding assessors and participants from localised

measurement devices. However, greater effort should be made in regards to the

randomisation of measurement devices and sites.

3.4.2 Summary of Findings

This systematic review sought to identify any measurement discrepancies

between conductive and infrared 𝑇sk measurement. Any clinically significant

differences between devices would inform exercise scientists and sports medicine

clinicians regarding the use, or validation, of these devices in clinical or research

settings. Overall, five studies found clinically significant differences (>0.5 °C)

between 𝑇sk measurements (Buono et al., 2007; Roy et al., 2006b; Ruopsa et al.,

2009; van den Heuvel et al., 2003), four studies reported overall differences between

0.1 to 0.5 °C (Burnham et al., 2006; Fernandes et al., 2014; Kelechi et al., 2011;

Kelechi et al., 2006; Matsukawa et al., 2000) and the remaining study did not report

mean differences between devices (Korukçu & Kilic, 2009).

Based on the included studies there appears to be no trend for conductive or

infrared devices to systematically overestimate or underestimate 𝑇sk. In some cases

conductive devices tended to measure higher 𝑇sk than infrared (Burnham et al., 2006;

Fernandes et al., 2014; Matsukawa et al., 2000; Ruopsa et al., 2009; van den Heuvel

et al., 2003), in other cases infrared instruments tended to measure higher than

conductive (Buono et al., 2007; Fernandes et al., 2014; Kelechi et al., 2011; Kelechi

et al., 2006; Roy et al., 2006b). It is plausible that the heterogeneity in the

methodological designs of the included studies led to the contrasting findings in the


current review; more specifically, the absence of standardisation for skin temperature

sites, device employment and environmental conditions.

In the studies where conductive overestimation of 𝑇sk was observed, it would

most likely be attributed to the microenvironment created by fixation to the skin,

increasing the 𝑇sk directly below the measurement probe (Buono & Ulrich, 1998;

Psikuta et al., 2013; Tyler, 2011). This insulation of the measurement area blunts the

skin capacity to remove heat directly below the contact probe, artificially raising the

𝑇sk readings. The extent to which tape influences temperature measurements varies

on the amount applied (Tyler, 2011) and the type of tape used (Psikuta et al., 2013)

(e.g. adhesive woven fabric vs. permeable non-woven tape). The tendency for

infrared devices to measure lower 𝑇sk is supported by a recent review of temperature

measurements at several sites around the knee in over 2900 participants (Ammer,

2012). The included studies in the review by Ammer (2012) utilised a single

measurement technique and when pooled with comparable studies, it was noted on

average that regardless of health status, contact thermometers measured hotter knee

temperatures than that of infrared thermography (1 °C in healthy and up to 2 °C in

unhealthy).

Interestingly, in the three studies (Buono et al., 2007; Fernandes et al., 2014;

Kelechi et al., 2011) that recorded measurements at rest in a thermoneutral

environment, as well as applying an external stressor (i.e., exercise, localised cold

application), mean differences were augmented between devices after the

introduction of the additional variable. The influence to which an intervention (i.e.

exercise, ambient or localised temperature changes) exacerbates differences between

devices is largely unknown, with small sample sizes and limited literature comparing

instruments under these acute settings.

Fernandes et al. (2014) used a randomised crossover design to compare

thermocouples and an infrared camera on separate days. The ability to make accurate

comparisons between the two devices was dependent on the homogeneity of baseline

𝑇sk of the same person between the two testing days. The authors attempted to

control for the natural 24-hour circadian variation in 𝑇sk, by conducting testing at the

same time of day. However, day-to-day variations in skin blood flow (Sundberg,

1984) and 𝑇sk (Sarabia et al., 2008) have previously been reported in healthy subjects

even when time of day is controlled for. Therefore, it is possible that differences may


have been affected by the methodological design of the study. Nevertheless, there

seems to be a confounding factor that influences measurement differences between

conductive and infrared devices as a result of the commencement (Buono et al.,

2007; Fernandes et al., 2014) and cessation (Fernandes et al., 2014) of exercise.

3.4.3 Limitations and Future Research

The current review involved an exhaustive search based on a comprehensive

list of electronic databases and extensive supplementary searching; however, there

were some limitations. Studies included in this review were restricted to English; and

relevant articles may have been overlooked in the grey literature. Additionally, one

study (Buono et al., 2007) had data manually extracted from graphs and figures.

Although this was undertaken by independently by two reviewers, with

inconsistencies checked through reviewer consensus and a third party, it still serves

as an estimation of the mean difference.

The cooler end of the human physiological 𝑇sk range (<5 °C) is associated with

localised 𝑇sk damage (e.g., frost bite). The upper end (43 °C) represents the

maximum allowable localised 𝑇sk during occupational activities (International

Organisation for Standardisation, 2004b). The brevity of research comparing device

measurement accuracy along the limits of the 𝑇sk continuum is therefore concerning.

This should be a priority of researchers as these severe environmental and physical

conditions are where accuracy is critical for minimising potential injury (i.e., frost

bite, heat stress). Therefore, future research should compare and contrast differences

between an assortment of commonly used conductive and infrared devices through

the human 𝑇sk range, during rest, exercise and recovery, under different ambient

conditions (including cold exposure) to better understand the inaccuracies and

sources of error between conductive and infrared devices. Further to this, research

examining if differences between devices are exacerbated between sexes, health

status, population (young vs. elderly; lean vs. obese) and/or ethnicity is warranted.

3.5 CONCLUSIONS

The current evidence suggests that conductive and infrared devices are not

interchangeable or within the current clinical recommendations in resting conditions.

However, there is no trend for conductive or infrared devices to consistently

overestimate 𝑇sk in comparison to each other. Due to limited and ambiguous


findings, it is unclear if these techniques of assessing 𝑇sk provide similar values in

the presence of external (e.g., exercise) or environmental (e.g., cold/heat exposure)

stimuli. Until more conclusive evidence is available, exercise scientists and sports

medicine practitioners need to be cognisant that conductive and infrared devices may

not be interchangeable.

Chapter 4: Correction formula of infrared and conductive thermometry 59

Chapter 4: Correction formula of infrared and conductive thermometry

4.1 INTRODUCTION

It may be assumed that conductive and infrared devices are interchangeable

even in the absence of a gold standard skin temperature (𝑇sk) measurement and the

wide variety of measurement devices available on the market. Provided one device

has been validated against a reference standard or certified thermometer, for any

other device to be considered interchangeable, temperature differences should not

exceed the proposed clinical significant difference of 0.5 °C (Kelechi et al., 2011).

This relativity small temperature difference represents the maximum allowable

disagreement between 𝑇sk measurement devices and any deviation outside of these

limits could influence the interpretation of results, diagnosis and therefore treatment

outcomes. For example, it has been shown that asymmetries in 𝑇sk >0.5 °C in post-

operative knee joints represents abnormalities which potentially affect therapeutic

management (Mayr, 1995) and that the same asymmetrical differences were first

successfully used as a diagnostic tool for tibial stress fractures (Goodman et al.,

1985).

Despite a documented failing for manufacturers of 𝑇sk devices to meet

accuracy claims (Foto et al., 2007; Jutte, Knight, & Long, 2008; Jutte et al., 2005;

Long et al., 2010; Versey et al., 2011), it is common for studies measuring 𝑇sk not to

calibrate the instruments against a known criterion before use. For instance, a brief

review of the literature reveals that 71 papers published between 2001 and 2013 in

the Journal of Applied Physiology reported human 𝑇sk as a primary outcome

variable. Of these only four studies (<6%; Brajkovic & Ducharme, 2003; Brajkovic,

Ducharme, & Frim, 2001; Jay et al., 2007; Peter, 2003) reported that any form of

calibration was conducted on 𝑇sk devices before human data collection. Typically,

water bath calibration is used as the gold standard for research laboratories to test the

validity, reliability and to quantify linear regression coefficients of conductive 𝑇sk

devices such as thermistors, iButtons® and thermocouples (Harper Smith et al., 2010;

van Marken Lichtenbelt et al., 2006); as well as core temperature measures including

60 Chapter 4: Correction formula of infrared and conductive thermometry

rectal thermometers (Casa et al., 2007; Ganio et al., 2009; Mannara et al., 1993) and

ingestible temperature pills (Hunt and Stewart, 2008). This calibration of

thermometry devices at regular intervals has been shown to improve accuracy of

aging instruments and ensures their sensitivity and specificity is preserved for the

diagnosis of various conditions and pathologies (Machin, Simpson, & Broussely,

2009; Simpson, Machin, McEvoy, & Rusby, 2006; Wood, Mangum, Filliben, &

Tillett, 1978).

In contrast, infrared 𝑇sk devices (infrared video cameras and infrared

thermometers) are calibrated against a blackbody source (Foto et al., 2007).

However, these devices are often made to test temperatures outside the human

physiological 𝑇sk range and are typically in excess the budget of most researchers

and clinicians. This expense has seen researchers develop novel and more affordable

means of calibration for infrared techniques (Hetsroni, Gurevich, Mosyak, &

Rozenblit, 2003; Horwitz, 1999; Ochs, Horbach, Schulz, Koch, & Bauer, 2009).

Consequently, researchers have used stirred water baths for the calibration of

infrared devices prior to human thermoregulatory investigations (Buono et al., 2007;

D. Ng et al., 2005; Plassmann, Ring, & Jones, 2006). Therefore, the purposes of this

investigation were to i) compare and contrast the validity of four commonly used

contact and infrared devices in a stirred water bath, ii) to develop a calibration

coefficient for all devices to improve measurement accuracy in the assessment of

their interchangeability for human 𝑇sk measurements (see Chapter 5), and iii) to

identify the most accurate device to use as a comparative standard for a human skin

temperature investigation (see Chapter 5).

4.2 METHODS

4.2.1 Experimental overview

Four devices, two conductive and two infrared, were calibrated against a

certified thermometer (ThermoProbe Inc., Pearl, Mississippi, USA). The

thermometer, which was suspended in the water bath, served to compare the devices

against a reference standard (Hunt & Stewart, 2008). The conductive devices

included eight thermistors (TM) (Grant Instruments, Cambridge, UK) and eight

iButtons® (IB) (Maxim Intergrated, Sunnyvale, California, USA) and the infrared

devices included a hand held thermometer (IT) (Tecnimed Inc., Varese, Italy) and a


thermal imaging camera (IC) (FLIR Systems, Wilsonville, Oregon, USA). Detailed

information regarding the specifications of all devices is presented in Table 4.1.

Table 4.1.

Device specifications

IR = Infrared. All specifications were derived from the corresponding company websites: a = http://www.thermoprobe.net/docs/data_TL1W.pdf; b = http://www.grantinstruments.com/media/5118/temperature_and_humidity_probes_june_2011.pdf; c = http://datasheets.maximintegrated.com/en/ds/DS1922L-DS1922T.pdf; d = http://www.flir.com/cs/emea/en/view/?id=41966; e = http://www.visiofocus.com/specificheEN.html.

A circulating water bath was used to test devices across eleven water

temperatures that encompassed the human skin physiological range (22, 24, 26, 28,

30, 32, 34, 36, 38, 40, 42 °C). This temperature range was selected to represent the

lowest expected ‘normal’ resting 𝑇sk in a thermoneutral environment (Niu et al.,

2001; Zaproudina et al., 2008), through to the upper range of 𝑇sk during exercise and

internationally standardised occupational limits (International Organisation for

Standardisation, 2004b). The temperature in the water bath was stabilised for at least

5-min before all devices simultaneously measure temperatures at 10-second intervals

for 1-min (Hunt & Stewart, 2008; Jutte et al., 2008; Long et al., 2010). These seven

values were later averaged for statistical analysis in accordance with previous work

(Hunt & Stewart, 2008). The temperature variation in the water bath was less than

0.02 °C during recording; a level of variation similar to that previously reported

Device Certified Thermometer

Thermistor (Data Logger)

iButton® Infrared Camera Infrared Thermometer

Model TL1-W

EU-UU-VL5-0 (SQ2020-2F8)

DS1922L-F50 A305 sc Visiofocus 06400

Make ThermoProbea

Grant Instrumentsb

Maxim Integratedc FLIR Systemsd Tecnimede

Specifications

Range:

Sensitivity:

Uncertainty:

-10 to +160 °C

0.01 °C

±0.06 °C

-50 to +150 °C

0.01 °C

±0.1 °C

-40 to +80 °C

0.0625 °C

±0.5 °C

IR Resolution:

Spectral Range:

-20 to +350 °C

<0.05 °C

±2 °C

320 x 240 pixels

7.5-14 µm

+1 to +55 °C

0.1 °C

±0.3 at 20-35.9 °C ±0.2 at 36-39 °C ±0.3 at 39.1- 42.5 °C ±1.0 at 42.6-55 °C

http://www.thermoprobe.net/docs/data_TL1W.pdf

http://www.grantinstruments.com/media/5118/temperature_and_humidity_probes_june_2011.pdf

http://datasheets.maximintegrated.com/en/ds/DS1922L-DS1922T.pdf


(<0.025 °C and <0.05 °C) in the literature (Harper Smith et al., 2010; van Marken

Lichtenbelt et al., 2006). All testing was completed on the same day in a temperature

controlled room (22.7 ± 0.2 °C, 49.7 ± 3.3 % relative humidity and air speed <1 m/s)

which was illuminated by minimal LED lighting. The room was free of any electric

heat generators, wind drafts or external radiation (e.g., sunlight) which has been

reported to alter the accuracy of these devices (Ammer & Ring, 2005; Hildebrandt et

al., 2010).

4.2.2 Measurement Devices and Procedures

Thermistors

All available conductive devices found in our laboratory were used (8 TM’s

and 8 IB’s) to measure inter-device variability and to identify any defective devices.

The eight TM’s were connected to a data logger (Grant Instruments, Cambridge,

UK) that had its real-time clock synchronised with a laptop computer and IB’s. The

data logger was programmed to log the temperature every 10-seconds before

immersion. In preparation for testing the wires of the eight TM’s were taped over the

walls of a circulating water bath allowing the probes to hang submerged at an angle

of ~45°, ~2 cm from the bottom of the water bath. All immersed devices, including

the certified thermometer, were at least 1 cm apart and free from contact with the

shell of the water bath and each other, allowing water to flow freely around the

devices.

iButtons®

All eight IB’s were programmed prior to data collection to log every 10-

seconds at a resolution of 0.0625 °C via the accompanying USB to computer

receptor (DS9490R USB Port Adapter, DS1402D-DR8 Blue Dot Receptor, Maxim

Intergrated, USA). Once programmed each of the eight IB’s were suspended in water

by a length of sewing thread (300dtex, Sew-All Thread, Gütermann, Gutach im

Breisgau, Germany) tied around the circumference of the device, maintaining a set

distance of ~2 cm from the bottom of the water bath. Following the completion of

data recording the TM’s and IB’s were removed from the water bath, to terminate

logging and import the data to Microsoft Excel (Microsoft Office Professional Plus

2010, Microsoft, Redmond, Washington, USA).


Infrared Camera

Two investigators simultaneously recorded data from the IT and IC manually.

This mirrored the recordings in the submerged contact devices. The IC was

positioned on a tripod directly above and perpendicular to the surface of the water.

Due to fluctuations in the cameras internal sensors (Grgić & Pušnik, 2011; Ring et

al., 2007), the IC was allowed to stabilise for 60-min before measurements.

Distances from the water surface were controlled at 60 cm. The camera was

connected to a second time-synchronised laptop computer that was running FLIR

R&D software (version 3.4.13191.2001, FLIR Systems, Wilsonville, Oregon, USA).

Emissivity for the IC was manually set to 0.99, resembling that of water (Rees &

James, 1992). All of the post-processing analysis associated with the IC was

completed by the same trained investigator using the aforementioned software.

Infrared Thermometer

The IT was an affordable, commonly used, point and shoot device with an

internally set emissivity depending on the desired measurement surface (e.g., water,

human skin). The second investigator took measurements every 10-seconds

simultaneously with the other devices and manually recorded values from the devices

digital display. The IT was secured at a constant distance of 60 mm from the surface

of the water. Readings from both infrared devices were taken adjacent to the areas

surrounding the submerged contact devices to ensure only the water temperature, and

not the contact devices were measured.

4.2.3 Statistical Analysis

The difference between each device and the certified thermometer was

calculated. Bland-Altman plots were used to compare these differences against the

certified thermometer. Mean differences (MD), 95% confidence intervals (CI) and

limits of agreement (LoA) between devices and the certified thermometer were

calculated using the following equations:

MD = �∑ xn� − �

∑ CTn

�

where MD is mean difference, ∑x is sum of the devices recorded temperatures, ∑CT

is the sum of the certified thermometers temperatures and n is the number of

recorded temperatures (n=7);


CI = MD ± (1.96 ∙ SE)

where CI is 95% confidence interval, SE is standard error;

LoA = MD ± (1.96 ∙ SD)

where LoA is limits of agreement, SD is standard deviation.

Corresponding with maximum clinical significance (Joly & Weil, 1969;

Kelechi et al., 2011; Kelechi et al., 2006; Selfe et al., 2008), mean differences

between a device and the certified thermometer at a given temperature >0.5 °C were

classified as invalid. The device which recorded the lowest mean differences

compared to the certified thermometer across the range of tested temperatures was

classified as the most agreeable device.

Linear regression was conducted to determine the calibration formula for future

use in the human testing investigation (Chapter 5). R values are also reported in

Table 4.3, with categories used to interpret the r values described as: 0 = zero

correlation; 0.1 to 0.3 = weak correlation; 0.4 to 0.6 = moderate correlation; 0.7 to

0.9 = strong correlation; 1.0 = perfect correlation (Dancey & Reidy, 2007). For

demonstration purposes Bland-Altman plots for both contact devices were derived

from the least accurate from the eight respective samples; thermistor #5 (Figure 4.1a)

and iButton® #7 (Figure 4.1b) and analysed using SPSS (SPSS version 21.0, SPSS

Inc., Chicago, USA).

4.3 RESULTS

Mean differences, confidence intervals and limits of agreement between each

device and the certified thermometer across all temperatures are presented in Table

4.2. The mean differences ± standard deviation between the eight TM’s and the

certified thermometer were on average -0.03 ± 0.04 °C (range: 0.01 to -0.09 °C); the

eight IB were on average 0.23 ± 0.04 °C (range: 0.17 to 0.29 °C). While the IT and

IC recorded mean differences of -0.38 and 0.61 °C respectively. Limits of agreement

for the worst performing TM were -0.15 to -0.04 °C; 0.26 to 0.31 °C for the worst

performing IB; -0.92 to 0.15 °C for the IT and 0.44 to 0.78 °C for the IC (Table 4.2).

Independent calibration was conducted in order to define corrections formula,

based on linear regression, for each device. The TM slope calibration coefficients

averaged 1.003 ± 0.001 °C (range: 1.002 to 1.005 °C), the intercept averaged 0.08 ±


0.03 °C (range: 0.04 to 0.13 °C), and all Pearson correlations coefficients (r)

equalled 1. The IB slope calibration coefficients averaged 1.001 ± 0.002°C (range:

0.999 to 1.005 °C), the intercept averaged 0.27 ± 0.07 °C (range: 0.2 to 0.41 °C), and

all r values equalled 1. The slope, intercept and r were 1.042, 0.94, 1.0; and 1.01,

0.95, 0.999 for both the IT and IC respectively. The individual linear regression

formula and r values are presented in Table 4.3.


Figure 4.1. Bland–Altman plot of the certified thermometer and a) thermistor 5; b) iButton® 7; c) infrared thermometer; d) infrared camera across eleven water bath temperatures. Solid black line indicates the mean difference (MD); dashed lines represent the 95% limits of agreement (LoA).


Table 4.2.

Mean difference and measures of variation for all tested contact sensors in

comparison to the certified thermometer.

Device MDa (°C) SDb SEc Upper CId Lower CId Upper LoAe

Lower LoAe

TM 1 -0.05 0.02 0.01 -0.03 -0.06 0.00 -0.10 2 -0.01 0.02 0.01 0.01 -0.02 0.04 -0.06 3 0.01 0.01 0.00 0.02 0.00 0.04 -0.02 4 -0.03 0.02 0.00 -0.02 -0.04 0.00 -0.06 5 -0.09 0.03 0.01 -0.07 -0.11 -0.04 -0.15 6 -0.03 0.03 0.01 -0.02 -0.05 0.02 -0.09 7 0.03 0.02 0.01 0.04 0.01 0.07 -0.01 8 -0.08 0.03 0.01 -0.06 0.10 -0.01 -0.14

IB 1 0.23 0.01 0.00 0.24 0.22 0.25 0.21 2 0.21 0.02 0.01 0.22 0.20 0.25 0.18 3 0.17 0.01 0.00 0.18 0.16 0.20 0.14 4 0.26 0.03 0.01 0.29 0.24 0.33 0.20 5 0.22 0.02 0.01 0.24 0.21 0.26 0.19 6 0.21 0.02 0.01 0.22 0.19 0.25 0.17 7 0.29 0.01 0.00 0.30 0.28 0.31 0.26 8 0.21 0.02 0.01 0.23 0.20 0.25 0.18

IT -0.38 0.27 0.10 -0.20 -0.57 0.15 -0.92 IC 0.61 0.09 0.03 0.67 0.55 0.78 0.44

TM = Thermistor; IB = iButton®. Devices with bolded numbers were selected for

human investigation (Chapter 5): 1 = Neck; 2 = Scapular; 3 = Hand; 4 = Shin a MD: Mean difference. b SD: standard deviation of mean difference. c SE: standard error of mean difference. d CI: 95% confidence interval. e LoA: 95% Limits of Agreement.


Table 4.3.

Calibration formula for all devices.

Device MD (°C) Regression Formula r

TM 1 -0.05 𝑦 = 1.0033𝑥 – 0.0586 1.0 2 -0.01 𝑦 = 1.0034𝑥 – 0.1036 1.0 3 0.01 𝑦 = 1.0019𝑥 – 0.0679 1.0 4 -0.03 𝑦 = 1.002𝑥 – 0.0371 1.0 5 -0.09 𝑦 = 1.0042𝑥 – 0.04119 1.0 6 -0.03 𝑦 = 1.0039𝑥 – 0.0894 1.0 7 0.03 𝑦 = 1.0031𝑥 – 0.1305 1.0 8 -0.08 𝑦 = 1.0048𝑥 – 0.0764 1.0

IB 1 0.23 𝑦 = 0.999𝑥 – 0.1953 1.0 2 0.21 𝑦 = 1.0012𝑥 – 0.2518 1.0 3 0.17 𝑦 = 1.001𝑥 – 0.2048 1.0 4 0.26 𝑦 = 1.0046𝑥 – 0.4121 1.0 5 0.22 𝑦 = 1.001𝑥 – 0.2551 1.0 6 0.21 𝑦 = 1.0018𝑥 – 0.2678 1.0 7 0.29 𝑦 = 1.0𝑥 – 0.2877 1.0 8 0.21 𝑦 = 1.0014𝑥 – 0.258 1.0

IT -0.38 𝑦 = 1.0418𝑥 – 0.9388 1.0 IC 0.61 𝑦 = 1.0103𝑥 – 0.9461 0.9999

TM = Thermistor; IB = iButton®; MD = Mean Difference. Devices with bolded

numbers were selected for human investigation (Chapter 5). The following numbered

devices were used on the corresponding site through all human investigations

(Chapter 5): 1 = Neck; 2 = Scapular; 3 = Hand; 4 = Shin.

4.4 DISCUSSION

The objective of this study was to determine the validity of four commonly

used contact and infrared devices. Further to this we aimed to develop calibration

coefficients for all devices to improve measurement accuracy in the assessment of

their interchangeability for human 𝑇sk measurements (Chapter 5) and to identify the

most accurate device to use as a comparative standard for the human investigation

(Chapter 5).

To the best of our knowledge this is the first investigation that tested the

validity of four devices (two conductive and two infrared) commonly employed in

the assessment of 𝑇sk against a certified thermometer in a water bath. The key


findings of this study show conductive devices are valid against a certified

thermometer and that infrared devices were approaching (infrared thermometer) or

greater than (infrared camera) the outlined minimal clinical significance (>0.5 °C).

These results suggest that the infrared devices used in this study may be an

inaccurate means of calculating 𝑇sk without prior calibration.

Thermistors and iButtons®

Mean differences of the TM’s and IB’s support the results of previous

investigations for similar devices (Harper Smith et al., 2010; van Marken Lichtenbelt

et al., 2006). Harper Smith et al. (2010) conducted an experiment with 28 TM’s and

46 IB’s comparing measurement differences against a certified thermometer in a

water bath. Mean differences between the TM’s, IB’s and the certified thermometer

were significantly different, 0.045 °C and 0.121 °C respectively. Although these

differences were statistically significant (P < 0.05), clinical significance (>0.5 °C)

was not breached. In the present study, differences between worst performing TM

and IB and the certified thermometer were not clinically significant, 0.094 °C and

0.288 °C respectively. Results indicate that the TM is the most accurate device tested

against the certified thermometer, and therefore has been identified as the most

appropriate comparative device for human skin investigation (Chapter 5).

Infrared Thermometer and Infrared Camera

Previous investigations measuring water bath surface temperature with IT’s

have found mean differences to be as high as 2 °C (D. Ng et al., 2005). The current

investigation found that the handheld IT measured temperatures within its

manufacturer claimed error between 22 and 30 °C (±0.3 °C between 20 and 35.9 °C).

Yet as water bath temperatures exceeded 32 °C, the uncertainty surpassed

manufacturer claims (±0.2 °C between 36 and 39 °C; ±0.3 °C at 39.1 and 42.5 °C)

and approached 0.8 °C between 36 to 42 °C. Measurement error increased linearly

with temperature, and was greatest at the upper limit tested (42 °C). This is of

particular concern as during real world applications, accuracy is essential at these

higher physiological temperatures where the risk of infection, inflammation, heat

illness or injury is greatest.

The IC had a manufacturer uncertainty of ±2 °C, which is approximately 20%

of the human 𝑇sk continuum from thermoneutral rest (~20 °C) through to the safe

limits in hot environments (43 °C). This suggests thermal cameras with similar


manufacturer uncertainty might not be sufficient for human applications without

calibration prior to data collection. In this study, the IC’s mean difference was 0.61 ±

0.09 °C and was consistently reproduced across all temperatures. This error was

within the manufacturer claimed accuracy but exceeded clinical significance.

4.4.1 Limitations and Future Research

Despite water bath calibration being widely used as a calibration technique for

contact 𝑇sk instruments, the conductivity and heat capacity of water is greater than

that of the human skin. In addition, during human tissue measurements only a portion

of the device is in contact with the skin as opposed to being completely immersed in

the water bath. Consequently, although our findings show each of the conductive

instruments are valid, both of these factors could reduce the mean difference scores.

In relation to the infrared devices, despite both being marketed with capabilities to

measure water temperatures, the influence of water vapour evaporating off the

measurement surface is currently unknown. Although the effect of water vapour on

infrared measurements is unlikely as both positive and negative mean biases were

observed for each of the infrared devices. Future studies should compare any

potential differences in calibration factors for infrared devices derived from both

certified water baths and black body devices.

It should also be noted that only four types of devices were tested and our

findings might not be applicable to the all makes and models of skin measurement

instrumentation on the market. Conclusions drawn from this study could also be

affected by the small sample tested of each type of device. However, it would not be

feasible to purchase multiple, expensive infrared devices and the purpose of this

study was to examine the most commonly used in a clinical/research setting.

Further investigation is necessary to determine any differences between

conductive and infrared devices when applied to human skin, and what influences

temperature differences between devices during cold and heat exposure,

thermoneutral, exercise and recovery conditions (see Chapter 5).

4.5 CONCLUSION

Overall, conductive temperature devices tested in this study were validated

against a certified thermometer. However, infrared devices were not validated

against the certified thermometer. These findings justified the calibration of all types


of the devices against a certified thermometer through the expected physiological

range of 𝑇sk before experimental data collection. The TM was classified as the most

accurate device and subsequently will be used as the comparative device for Chapter

5.

Chapter 5: Mean skin temperature assessment during rest, exercise in the heat and recovery: differences between conductive and infrared devices 73

Chapter 5: Mean skin temperature assessment during rest, exercise in the heat and recovery: differences between conductive and infrared devices

5.1 INTRODUCTION

The measurement of human thermoregulatory responses to environmental

extremes and exercise is of great interest to health professionals and researchers.

Historically, the measurement of human skin temperature (𝑇sk) via contact

(conductive) devices has been widely regarded as the primary measurement

technique in clinical, exercise science and research settings. However, contact

methods of 𝑇sk measurement present researchers with a number of potential

methodological limitations including: wire entanglement (van Marken Lichtenbelt et

al., 2006), loss of sensor contact during exercise (Buono et al., 2007), the formation

of a microenvironment around the sensor as a result of fixation method (Buono &

Ulrich, 1998; Tyler, 2011) and spot measurements (Costello, McInerney, et al.,

2012). The advent of more innovative non-contact technology has seen infrared

devices (e.g., handheld infrared thermometers and infrared cameras) become widely

accepted as techniques of assessing 𝑇sk in an attempt to overcome some of the

limitations associated with contact devices (Costello et al., 2013; Kelechi et al.,

2006; E. Ng, 2009).

To be considered clinically interchangeable mean differences between two

calibrated skin temperature instruments cannot exceed 0.5 °C (Joly & Weil, 1969;

Kelechi et al., 2011; Kelechi et al., 2006; Selfe et al., 2008). Unfortunately, despite

widespread use throughout clinical and research settings, the scientific evidence

supporting the interchangeability of infrared thermometry with more traditional

conductive instruments is limited and equivocal (Buono et al., 2007; Burnham et al.,

2006; Edge & Morgan, 1993; Hershler, Conine, Nunn, & Hannay, 1992; Kelechi et

al., 2011; Korukçu & Kilic, 2009; Matsukawa et al., 2000; Roy et al., 2006b; Ruopsa

et al., 2009; van den Heuvel et al., 2003).

74 Chapter 5: Mean skin temperature assessment during rest, exercise in the heat and recovery: differences between conductive and infrared devices

Few studies have compared the interchangeability between different

conductive devices during exercise in varying ambient conditions (Harper Smith et

al., 2010; van Marken Lichtenbelt et al., 2006). However, comparisons between

contact and non-contact devices during exercise have been largely neglected with

only two investigations comparing devices during rest and exercise (Buono et al.,

2007; Fernandes et al., 2014); with a single study measuring the effect of varying

ambient temperatures on device accuracy (Buono et al., 2007). Buono et al. (2007)

surmised that infrared thermometry is a valid means to measure mean skin

temperature (𝑇�sk) in rest and exercise in both hot and cold environments. However,

these suggestions were based on a comparison between thermistors and an infrared

thermometer. In addition, 𝑇�sk was not measured during participant recovery post

exercise. In a more recent study by Fernandes et al. (2014) recovery of 𝑇�sk from

exercise under thermoneutral conditions was evaluated with both an IC and TC’s.

Differences between the IC and TC’s were significant during rest (0.75 ± 0.39 °C),

exercise (-1.22 ± 0.7 °C) and recovery (1.16 ± 0.66 °C) with the authors concluding

that there is poor correlation and low-reliability between the two measurement

modalities.

To our knowledge, no study has examined a range of devices commonly used

to assess 𝑇�sk during exercise in a hot and humid environment and post-exercise

recovery. Therefore, the purpose of this study was to systematically evaluate the

interchangeability of four devices – two conductive (thermistors [TM] and iButtons®

[IB]) and two infrared (infrared thermometer [IT] and infrared camera [IC]) – in the

assessment of 𝑇�sk during rest, exercise in the heat and subsequent recovery. It was

hypothesised that under all conditions, the conductive and infrared devices tested

would be considered clinically interchangeable (error ≤0.5 °C) with the comparative

thermistor.

5.2 METHODS

5.2.1 Participants

After ethical approval from the Human Research Ethics Committee

(Queensland University of Technology) (Appendix A) a convenience sample of 30

healthy males participated in this study. Prior to commencing the study all

participants completed a health screen questionnaire (Appendix B) and provided


signed informed consent (Appendix C). Contraindications for participation included

a history, or current existence of any cardiopulmonary disease, acute skin conditions

(e.g. adhesive allergy), any metabolic, arterial, venous or lymphatic pathology,

current history of smoking, or the use of any medication that alters cardiovascular

function or thermoregulation.

Participant demographic and anthropometric characteristics are presented in

Table 5.1. Height was measured with a stadiometer to the nearest 5 mm, with shoes

removed in an upright posture and during inhalation. Digital scales (Wedderburn

BWB-600, Tanita Corporation, Tokyo, Japan) were used to measure body mass to

the nearest 50 grams. An International Society for the Advancement of

Kinanthropometry (ISAK) accredited examiner recorded the sum of skinfolds taken

at 8 anatomical locations on the right hand side of the body (tricep, sub scapular,

bicep, iliac crest, supraspinale, abdominal, front thigh, medial calf) using a

Harpenden skinfold caliper (British Indicators Ltd, Weybridge, UK). All measures

were duplicated with the average of the two measurements representing the site; with

a third measurement taken if differences between the first two values were greater

than 5%.

Table 5.1.

Participant characteristics, values are mean ± standard deviation (range).

Age (years) Body Mass (kg) Height (cm) ∑ of 8 Skin Folds (mm) BMI (kg·m-2)

25.0 ± 2.9 (18.7 - 32.8)

78.7 ± 11.4 (50.8 - 113.2)

181.3 ± 8.3 (168.0 - 208.9)

88.94 ± 32.3 (41.1 - 145.3)

23.9 ± 2.2 (17.6 - 28.5)

BMI: Body mass index.

5.2.2 Pre-experimental Protocol

Participants were instructed to avoid prolonged sun exposure five days prior to

the testing day (to prevent sunburn). Where appropriate, any measurement site with

exposed hair was shaved at least 36 hours before testing, to prevent inflammation or

damage to the skin surface from the razor artificially raising skin temperature (Merla

et al., 2010). To ensure compliance participants were contacted two days prior to

testing. On the day of testing participants were required to keep the measurement

sites clean of ointments and cosmetics. In preparation for testing participants did not

engage in exercise, ingest caffeine or alcohol 24 hours prior to testing (Ammer &

Ring, 2006); or have a hot shower within two hours of arriving to the laboratory.


Two hours before the trial commenced, participants were asked to consume a light

meal with 500 mL of water. Clothing was instructed to be unencumbering and

conducive to exercise.

5.2.3 Experimental Protocol

All testing took place in a sub-tropical location in Australia’s Spring season

(September and October), beginning at either 0900 h or 1400 h and lasted

approximately three hours. Volunteers entered the controlled laboratory from

outdoor temperatures of 23.1 ± 2.0 °C and 58 ± 10 % relative humidity at 0900 h and

25.8 ± 2.1 °C and 51 ± 9 % relative humidity at 1400 h. The primary outcome in the

current study was within subject variation in the four devices. We were not interested

in between subject variability and therefore, different time of day was not considered

a confounder in the analysis.

Upon arrival the testing protocol was explained to all participants, any

questions were answered, and informed verbal and written consent was acquired

(Appendix C). Initially the four skin temperature measurement sites (Figure 5.1)

were cleaned with rubbing alcohol to remove any oils or other residual contaminants

influencing skin emissivity (Bernard et al., 2013). During environmental acclimation

and data collection participants wore only training shoes, socks, shorts and a heart

rate monitor.


Figure 5.1. Four skin temperature measurement regions of interest in accordance with International Organisation for Standardisation - 9886. 1) back of neck; 2)

inferior border of right scapula; 3) dorsal right hand; 4) proximal third of right tibia.

Data collection consisted of repeated 𝑇sk measurements taken by four

commonly used instruments (Table 5.2), during three sequential periods of rest,

exercise in the heat and recovery (Figure 5.2). Acclimatisation, resting and recovery

took place in a temperature controlled, fluorescently lit room without the existence of

electric heat generators, wind drafts or external radiation (i.e. sunlight). The exercise

protocol was completed in a climate chamber (dimensions 4 x 3 x 2.5m; length,

width, height). Skin temperatures, ambient temperature and relative humidity (with

digital weather station: 3M QuestTEMP 36, 3M, St. Paul, Minnesota, United States),

and air speed (with digital anemometer: Kestrel Pocket Weather 4000, Nielsen-

Kellerman, Boothwyn, Pennsylvania, USA) were measured at 3 minute intervals

during rest, exercise and recovery periods.


Figure 5.2. Timeline of data collection protocol. 𝑇�sk = Mean Skin Temperature; TM

= Thermistor; IB = iButton®; IT = Infrared Thermometer; IC = Infrared Camera.

Rest

Following a conventional 20-min acclimatisation (Hart & Owens Jr, 2004; Roy

et al., 2006a), resting measurements were taken during 30-min of seated rest in a

thermoneutral environment (24.0 ± 1.3 °C, 56 ± 9 % relative humidity, <0.1 m/s air

speed). Participants were seated on an adjustable stool for the duration of the

acclimatisation, resting and recovery periods. Seated position consisted of an upright

posture, feet flat on the floor, forearms resting on the thighs and the head consistent

with the Frankfurt plane. At the beginning of the acclimatisation period and at the

commencement of exercise, participants were given 250 mL of room temperature

water for a total fluid consumption of 500 mL.

Exercise

The exercise protocol was conducted on a Monark cycle ergometer (Ergomedic

824E, Monark, Vansbro, Sweden) with 1 kilogram loaded on a 500 g weighted

basket for a total resistance of 2.0 kg at 60 revolutions per minute (2.0 kp at 60

rev·min-1 = 120 watts). Ambient conditions were controlled at 38.0 ± 0.5 °C, 41 ± 2

% relative humidity and a wind speed of 0.5 ± 0.1 m/s. This type of condition was

chosen to induce large 𝑇sk changes and resembled similar investigations (Buono et

al., 2007; Harper Smith et al., 2010; van Marken Lichtenbelt et al., 2006). All

subjects were able to achieve this workload for the required 30-min.

Recovery

Following exercise, participants returned to seated rest in the thermoneutral

observation room (24.0 ± 1.3 °C, 56 ± 9 % relative humidity, <0.1 m/s air speed) for

45-min of data collection.


5.2.4 Measurements and Equipment:

Skin Temperature

Four measurement devices were used to assess skin temperature (Table 5.2);

two contact devices: thermistor (TM) (Grant Instruments, Cambridge, UK) and

iButton® (IB) (Maxim Intergrated, Sunnyvale, California, USA); and two non-

contact devices: infrared camera (IC) (Tecnimed Inc., Varese, Italy) and handheld

infrared thermometer (IT) (FLIR Systems, Wilsonville, Oregon, USA). The TM, IB

and IT were new, unused devices while the IC was serviced and calibrated by the

manufacturer prior to the commencement of this study. Additionally, all devices

were previously calibrated against a NIST-certified thermometer in a stirred water

bath before human investigation (Chapter 4). The resultant calibration formula was

applied to the recorded values following human data collection (see Chapter 4, Table

4.3).


Table 5.2.

Device specifications

IR = Infrared. All specifications were derived from the corresponding company websites: a = http://www.grantinstruments.com/media/5118/temperature_and_humidity_probes_june_2011.pdf; b = http://datasheets.maximintegrated.com/en/ds/DS1922L-DS1922T.pdf; c = http://www.flir.com/cs/emea/en/view/?id=41966; d = http://www.visiofocus.com/specificheEN.html.

Contact Devices

Because of minimal differences found within each of the TM and IB during

water bath calibration (Chapter 4) the first four of the eight calibrated devices were

selected for this investigation. The four TM were connected to an associated data

logger (Grant Instruments, Cambridge, UK) and laptop computer that was used to

time synchronise both the TM and IB. Before application to the participant the data

logger and four associated TM were preprogramed to log every 2-seconds. All IB

were pre-programmed via the accompanying USB to computer receptor

(DS9490R USB Port Adapter, DS1402D-DR8 Blue Dot Receptor, Maxim

Integrated, Sunnyvale, California, USA) and time synchronised with the TM to log

Device Thermistor (Data Logger)

iButton® Infrared Camera Infrared Thermometer

Model EU-UU-VL5-0 (SQ2020-2F8)

DS1922L-F50 A305 sc Visiofocus 06400

Make Grant Instrumentsa Maxim Integratedb FLIR Systemsc Tecnimedd

Specification Range:

Sensitivity: Uncertainty:

-50 to +150 °C 0.01 °C ±0.1 °C

-40 to +80 °C 0.0625 °C ±0.5 °C

IR Resolution:

Spectral Range:

-20 to +350 °C <0.05 °C ±2 °C 320 x 240 pixels 7.5-14 µm

+1 to +55 °C 0.1 °C ±0.3 at 20-35.9 °C ±0.2 at 36-39 °C ±0.3 at 39.1-42.5 °C ±1.0 at 42.6-55 °C


every 2-seconds at an 11-bit resolution of 0.0625 °C. Details regarding the

application of contact devices to the participants are discussed further in this section

under Regions of Interest. Once testing was completed, both the TM and IB were

removed from the participant to terminate logging and import all data into Microsoft

Excel (Microsoft Office Professional Plus 2010, Microsoft, Redmond, Washington,

USA).

Non-contact Devices

Infrared skin temperature measuments were taken by two researchers; one

recorded values from the infrared thermometer and the other the infrared camera

measures. The IT is a relatively cheap, point and shoot device commonly employed

in clinical settings. For measurements the IT was held 90° from the skin’s surface

with the aid of spacing rods that were added to the casing of the device (Roy et al.,

2006b). This kept the device at a constant distance of 60 mm from the skin. The

device was equipped with a manual internal re-calibration for large changes in

ambient temperatures. When moving between thermoneutral to hot, and hot to

thermoneutral conditions, the IT was re-calibrated to the ambient conditions prior to

any readings. During exercise on the bike, one researcher measured the temperatures

at each of the four skin sites within a 15-second period. While the other researcher

recorded the time (hh:mm:ss) of each recording, to ensure accurate comparison to

logging contact devices. During the shin regions temperature measurement

participants were asked to stop pedalling (approximately 3 to 5-seconds) so the IT

could record the site temperature.

The IC was set up on a level tripod perpendicular to the seated, resting

participant at a distance of approximately 0.8 to 1.1 m depending on the height and

size of the participant (Ammer, 2003, 2008; Ammer & Ring, 2006). The camera was

set up and allowed to stabilise for at least 60-min prior to subject arrival (Grgić &

Pušnik, 2011). Any required adjustments needed to fit the regions of interest within

the IC field of view resulted from the manipulation of chair height and its distance

from the camera. In order to assure high quality images, auto-focusing of the

camera’s field of view was performed prior to the capture of each thermal image.

Each image was time stamped for accurate post-processing of images. Post-

processing FLIR R&D software (version 3.4.13191.2001, FLIR Systems,

Wilsonville, Oregon, USA) was used to input recorded variables such as ambient


temperature, relative humidity, camera distance and a constant skin emissivity of ε =

0.98 in accordance with previous research (Boylan et al., 1992; Sanchez-Marin et al.,

2009; Steketee, 1973; Togawa, 1989). The selection of the region of interest was

made with the variable rectangle tool to select all pixels within the distinct area

outlined by the aluminium tape (see Regions of Interest).

𝑇�sk was derived from three thermal images that encompassed four regions of

interest (Figure 5.3) taken within a 30-second period. The corresponding IT

measurement was taken by the second researcher simultaneously to the thermal

image at a given site. A stopwatch synchronised to the computer was used to ensure

manual recordings by researchers matched the autonomously logging contact

devices. The time of recordings (hh:mm:ss) were scribed for accurate retrospective

data extraction from the contact devices.

Methodological constraints prevented the use of the IC during exercise

conditions. These included potential measurement error from the camera by

physically moving it between each phase of testing, before adequate stabilisation

time of at least 30-min (Grgić & Pušnik, 2011). In addition, it seemed impractical to

require the subject to cease exercising and dismount from the cycle ergometer every

3-min to take the required photos. As a result, only the three other types of devices

were compared in the exercise condition.


Figure 5.3. Example of regions of interest captured via infrared thermography. a) Hand b) Neck and Scapula c) Shin.

Regions of Interest

Measurements were taken at four body locations (back of neck, inferior border

of right scapula, dorsal right hand and proximal third of right tibia) in accordance

with ISO 9886 (International Organisation for Standardisation, 2004b). The readings

from these sites were used to calculate 𝑇�sk using the following equation

(International Organisation for Standardisation, 2004b): 𝑇�sk = (Tneck*0.28) + (Tscapula*0.28) + (Thand*0.16) + (Tshin*0.28)

Where Tneck represents the skin temperature (°C) of that region and the

numerical value (e.g. 0.28) is the weighted value applied to that site.

A square template marking the placement of devices was drawn on the skin at

each of the four skin temperature sites (Figure 5.4a). Within the marked square were

four 25 mm x 25 mm quadrants, with each representing a measurement site for one

of the four devices (Figure 5.4b). In order to account for any within site variation,


device allocation within a given quadrant was determined with a random number

generator.

Figure 5.4. a) Diagram of template dimensions used on each of the four skin sites; b) example of the randomised layout of marked and placed devices on a male subject’s shin; IB: iButton®, IT: Infrared Thermometer, TM: Thermistor, IC: Infrared Camera.

To maintain reliable placement of the contact devices to the skin, the same

researcher marked the region of interest and positioned the devices for each subject.

Throughout experimental testing, each contact device was marked with one of the

four sites (e.g. neck) and constantly placed upon the same site for each participant.

Contact devices were held in place with a single layer of Leuko sportstape

(Leuko, Beiersdorf, Hamburg, Germany) to reduce the influence of tape artificially

increasing temperatures (Buono & Ulrich, 1998; Tyler, 2011). Four 3 mm x 50 mm

strips of aluminium tape (3M, St. Paul, Minnesota, United States) were used as inert

markers and placed around the infrared camera quadrant to identify the region of

interest during post processing of the thermal images (Figure 5.4b).

5.2.5 Statistical Analysis

The data are displayed as mean ± SD unless otherwise stated. The response of

all devices was similar regardless of the measurement site and therefore, for the

purpose of this study 𝑇�sk was primary site for analysis (the complete graphed data set

is presented in Appendix D). Repeated measures analysis of variance (ANOVA) was

used to assess the effect of time, device, and device by time for all measured sites

and skin temperature (all outputs presented in Appendix E). All variables were tested

for normality via Shapiro-Wilks tests and where the assumption of sphericity was


violated, the Greenhouse-Geisser epsilon was used to adjust the degrees of freedom

to increase the critical values of the F-ratio. Statistical significance for the ANOVA

was set to P < 0.05.

Paired samples t-tests post-hoc analysis, using a Bonferroni correction, were

performed where significant differences between device and time were identified for

𝑇�sk across all three periods. Time points were selected for the beginning, middle and

end of the resting period, and every second time point from the start of the exercise

and recovery periods. Without the presence of a gold standard for skin temperature

measurement, the TM was used as the comparative device in which differences

between all other devices were tested (outputs and comparisons between all devices

are presented in Appendix F). The TM was identified as the comparative device for

this investigation was due to its performance against the certified thermometer in the

previous water bath calibration (Chapter 4). All data was analysed using SPSS (SPSS

version 21.0, SPSS Inc., Chicago, USA).

5.3 RESULTS

A significant main effect for device by time was observed in all three periods

for 𝑇�sk (Rest: F30,870=2.734, P=0.004, 1-β=0.96; Exercise: F20,580=155.54, P < 0.001,

1-β=1.00 and Recovery: F30,870=125.08, P < 0.001, 1-β=1.00). Pairwise comparisons

of 𝑇�sk revealed significant differences (P < 0.001) between TM and IT, and TM and

IC during resting conditions, and significant differences (P < 0.001) for comparisons

between the TM and all other devices tested during exercise and recovery. Mean

differences between TM and IB are as follows: rest = -0.01 °C, exercise = -0.25 °C,

recovery = -0.37 °C; the TM and IT: rest = -0.34 °C, exercise = 0.46 °C, recovery = -

1.04 °C; TM and IC: rest = -0.83 °C, recovery = -0.188 °C. Post-hoc analysis of

individual time points for clinical and statistical significance differences between the

TM and the other devices are indicated in Figure 5.5.


Figure 5.5. Mean skin temperature (n=30) of all tested devices during rest (4 devices), exercise (3 devices) and recovery (4 devices). a = IB clinically (>0.5 °C) and significantly (P < 0.001) different from TM; b = IT clinically (>0.5 °C) and significantly (P < 0.001) different from TM;

c = IC clinically (>0.5 °C) and significantly (P < 0.001) different from TM. TM: Thermistor; IB: iButton®; IT: Infrared Thermometer; IC: Infrared Camera.


5.4 DISCUSSION

The aim of this study was to evaluate 𝑇�sk differences measured by three

commonly used devices in comparison to a calibrated thermistor during rest, exercise

in the heat and passive recovery. It was hypothesised that under all conditions, the

conductive and infrared devices tested would be considered clinically

interchangeable (error ≤0.5 °C) with the comparative TM. Although comparisons

between 𝑇sk devices have been documented in the past (Buono et al., 2007; Burnham

et al., 2006; Harper Smith et al., 2010; Hershler et al., 1992; Kelechi et al., 2011;

Kelechi et al., 2006; Korukçu & Kilic, 2009; Matsukawa et al., 2000; Roy et al.,

2006b; Ruopsa et al., 2009; van den Heuvel et al., 2003; van Marken Lichtenbelt et

al., 2006), no study has systematically evaluated the interchangeability between

infrared and conductive instruments during rest, exercise and recovery. The key

findings of this study include: (1) the IC was not interchangeable with the

comparative TM device during rest or recovery; (2) it should not be assumed that

devices within acceptable agreement during resting conditions will continue to agree

during exercise and recovery; and (3) clear systematic errors exceeding statistical and

clinical (>0.5 °C) significance are present between conductive and infrared devices

throughout all conditions. These findings are in direct contrast to our hypothesis,

namely that infrared and conductive devices would not exceed clinical significance

under all conditions. For the purpose of this discussion comparisons between devices

will be covered separately for each of the three periods.

Rest

The present results indicate that 𝑇�sk measured by IC is significantly different to

that measured by TM’s, and with mean differences >0.5 °C the IC would not be

considered interchangeable under medical or scientific applications. Across all time

points measured during the rest period, even after calibration, the IC consistently

overestimated 𝑇�sk compared to the TM by an average of 0.83 ± 0.39 °C. Significant

differences preventing the interchangeability of IC and TM have been observed

previously (Fernandes et al., 2014; van den Heuval et al., 2003). However,

differences in the current study of 0.83 ± 0.39 °C are not consistent with the earlier

study by van den Heuvel et al. (2003), where a previously calibrated IC

underestimated 𝑇sk when compared to a TM, with mean differences of -2.32 ± 0.54

°C. Discrepancies between this previous study and the present investigation could be


explained by methodological differences such as data collection and instrument

makes/models. More specifically, in the study by van den Heuvel et al. (2003) 𝑇sk

was not recorded simultaneously. The thermistor values were averaged from a

recording frequency of 1 Hz over a 30 second period, while infrared camera images

were taken at a single time point within the same 30 second period. Furthermore, TM

were attached with a ‘minimal amount’ of collodion adhesive glue under the sensor

head and post image analysis selecting the skin ‘immediately adjacent’ to the TM tip.

In combination with any subjective variance for selecting this ‘adjacent area’

between repeated IC images during post processing analysis, any excess adhesive

dispersing outside of the TM tip could cause the IC to measure the temperature of the

adhesive on the skin and not the skin itself. In a more recent investigation, Fernandes

et al. (2014) found infrared camera overestimated 𝑇�sk measure by a thermocouple by

0.75 ± 0.39 °C during rest in a thermoneutral environment, which is similar to that of

the current investigation (0.83 °C). Nevertheless, in each study the IC would not be

considered interchangeable with more traditional conductive means of 𝑇sk

measurement under stable resting conditions as seen in clinical and research settings.

In contrast, satisfactory mean differences were observed between both the TM

and the IB, and the TM and the IT (Figure 5.5). Although others have reported

similar findings to the current study with differences between TM and IT of ≤0.5 °C

(Buono et al., 2007; Burnham et al., 2006; Hershler et al., 1992; Kelechi et al., 2011;

Kelechi et al., 2006), there have been studies approaching (Burnham et al., 2006;

Matsukawa et al., 2000) or exceeding (Roy et al., 2006b) clinical significance under

resting conditions. This investigation is the first to compare the IB against other 𝑇sk

devices in a resting stable thermoneutral (24 °C) environment. A similar study by

Harper Smith et al. (2010) compared IB’s to TM’s during rest and exercise in 10, 20

and 30 °C ambient temperatures with varying wind speeds. During the closest

comparative condition to our study (20 °C, 0.18 m/s), Harper Smith et al. (2010)

found that despite calibration, the IB’s mean differences between the IB and TM (0.7

± 0.02 °C) violated statistical and acceptable clinical limits. In the present

investigation, after individual calibration of devices, no clinical or significant

differences were found between the TM’s and IB’s under stable thermoneutral

conditions (mean differences of -0.01 ± 0.2 °C). One reason for this may be the

exposure to cooler ambient temperatures in the previous study. Additionally,


different methods of fixation and models of thermistors could potentially explain the

contrasting results.

Exercise

During exercise in the heat, considerable differences and temperature

fluctuations were observed between infrared and conductive measurement devices, in

contrast to our hypothesis. These differences are highlighted in Figure 5.5 with the IT

and IB’s differing in both clinical and statistical significance from the thermistor

temperatures at various points throughout exercise in the heat. Initial increases in 𝑇sk

while exercising in the heat are predominantly a function of ambient temperature and

are not significantly dependent upon workload (Stolwijk & Hardy, 1966). Therefore,

these initial differences observed between the three devices are most likely a result of

individual thermal inertia of the two conductive devices and the exposed skin

equilibrating to the change in ambient temperatures. The clinical and statistical

differences between the IB’s and TM’s at the start and towards the end of exercise

contradict previous observations (Harper Smith et al., 2010; Stolwijk & Hardy, 1966;

van Marken Lichtenbelt et al., 2006). We propose dissimilar findings could be due to

a number of factors. As a result of the high thermal strain involved in our study

(38°C, 40% relative humidity), it is likely that the skin of the participants became

saturated with sweat as testing progressed and the tape holding the conductive

devices in place absorbed the sweat, altering its evaporative and thermal conductivity

(Psikuta et al., 2013). The influence in which the sweat covered tape had on each

device would be a product of the shape, size and material properties (i.e. copper vs.

aluminium) of both TM’s and IB’s. The effect of sweat saturating the tape is best

illustrated during the recovery period whereby differences between each conductive

device equalise as the sweat evaporates during resting conditions (75–108th minute,

Figure 5.5).

Some evidence suggests that IT agrees sufficiently with traditional TM for the

measurement of 𝑇sk in the presence of environmental stressors (Buono et al., 2007;

Kelechi et al., 2011; Psikuta et al., 2013). This investigation found low agreement

and significant differences between the IT and TM’s during exercise in the heat. The

amplified differences seen between the infrared thermometer and thermistors as

exercise progressed may be a product of cooler sweat pooling and evaporating from

the surface of the skin. Consequently, this would likely prevent the IT from


measuring accurate skin temperatures (Bernard et al., 2013). Moreover, the

insulating characteristics of the tape covering the conductive devices would create an

insulating microenvironment, limit evaporative cooling and therefore increase the

temperature relative to the exposed infrared measurement site (Buono & Ulrich,

1998; Tyler, 2011).

Despite not measuring 𝑇�sk with the IC during the exercise period, it is logical

to suggest that the IC would have been significantly influenced by the presence of

sweat along the skin surface with relative changes comparable to that of the IT.

Recent findings by Fernandes et al. (2014) whereby an IC progressively

underestimated 𝑇�sk throughout exercise relative to the comparative thermocouples (-

1.22 ± 0.7 °C) supports our postulation. This effect has also been observed in IC in

which liquids present along the skin surface cause significant underestimation of true

skin temperatures (Bernard et al., 2013). Moreover, even if relative, and not absolute,

changes in 𝑇�sk are of interest to researchers and exercise scientists, the use of infrared

devices may not be suitable in settings where the participant is subjected to hot

environments or exercise that induces a sweating response. Future research should

determine the influence of confounding factors such as sweat on both infrared and

conductive devices, by measuring localised sweat rates (Ohhashi, Sakaguchi, &

Tsuda, 1998; Smith & Havenith, 2012) during both exercise and recovery.

Recovery

To the best of our knowledge this is the first investigation that has compared

infrared and conductive devices for the calculation of 𝑇�sk during recovery from

exercise in the heat. The present findings demonstrate systematic differences

between conductive and infrared means of 𝑇sk measurement (Figure 5.5). Statistical

and clinical differences are present between the TM and both infrared instruments

throughout the recovery period. The recovery phase saw the greatest mean

differences between TM and every other device (IB = -0.37 °C; IT = -1.04 °C; IC

-1.88 °C). Similar results for the IC were observed by Fernandes et al. (2014) during

recovery from exercise in a thermoneutral environment, with the IC over estimating

skin temperatures by 1.16 °C. Similar contrasting relative changes in skin

temperature during exercise and recovery between conductive and infrared devices

were reported by Fernandes et al. (2014) and denote clear distinctions between the

scientific principles underlying conduction and radiation. Iit is logical to suggest that


the presence of sweat as a result of exercise in the heat plays a significant role in the

measurement differences observed in the current study. Differences between

conductive and infrared devices are greatest following 18-min of rest. As the sweat

evaporates from the tape covering the conductive devices, 𝑇�sk begins to converge,

but fails to return to baseline values after 45-min. Findings from this investigation

suggest that conductive and infrared devices cannot be used interchangeably during

recovery from hot conditions and report similar results to that of recovery following

exercise in thermoneutral temperatures (Fernandes et al., 2014). This limits

comparisons between a large portion of the exercise science literature, where

thermoregulatory responses are depicted differently between means of cutaneous

temperature measurement. Future studies should determine if similar differences are

seen during recovery from cold exposure.

Limitations

Due to the conductive devices being in direct contact with the skin,

comparisons made between devices were measured from sites adjacent to each other

and not a single point on the skin. Skin temperature variation within the

measurement area could contribute to measurement differences between devices

(Frim et al., 1990). However this is unavoidable as contact devices must cover the

area of skin they are measuring. Furthermore, as there are no standardised anatomical

placements for 𝑇�sk devices within a region of interest, we feel the uniform

measurement area (50 mm x 50 mm) and the randomised allocation of devices within

the area minimised errors associated with variation across the site.

Unfortunately this study was not able to compare measured 𝑇�sk using the IC

during exercise due to methodical constraints. IC’s require stabilisation to the

surrounding ambient conditions for accurate measurement (Grgić & Pušnik, 2011)

and because of changes in testing environments during rest, exercise and recovery,

stabilisation would not have been possible. Additionally, it is impossible to attain 𝑇sk

across numerous measurement sites with a single IC during dynamic exercise. A

plausible solution would be to use multiple cameras in each environment and around

the participant during exercise. However due to the large cost associated with IC this

is not a realistic alternative.


5.5 CONCLUSION

In conclusion, this investigation found that even after calibration, conductive

and infrared devices are not interchangeable under resting, exercise or recovery

conditions. More specifically, the IC consistently overestimated 𝑇sk outside clinical

and significant limits compared to the comparison TM. The results also indicate that

IB and IT are interchangeable with the TM under stable resting conditions. Though,

this interchangeability between the IT and TM is not maintained following exercise

in the heat or during recovery. It is proposed the presence of sweat results in

systematic errors between infrared and conductive devices due to the principles of

conductive and radiant heat measurement. It should be noted that the current findings

may not apply to all makes and models of skin thermometry, or to other ambient

conditions (e.g., cold exposure) or populations (e.g. elderly or females). In summary,

the current findings demonstrate that clinical and significant differences exist

between conductive and infrared devices which are commonly employed in the

assessment of human 𝑇sk.

Chapter 6: Conclusions 95

Chapter 6: Conclusions

Introduction

The primary aim of this thesis was to investigate the interchangeability of

conductive and infrared means of 𝑇sk measurement at rest in a thermoneutral

environment, during exercise in the heat and recovery (Chapter 5). Prior to the

investigation of this research question, a systematic review of the literature

pertaining to the interchangeability of conductive and infrared 𝑇sk devices (Chapter

3) was undertaken. The systematic review allowed for the objective development and

evaluation of a methodology that would appropriately answer this thesis’s primary

aim. This lead to a calibration study (Chapter 4) of four unique devices in order to

achieve two things: 1) to derive a correction formulae from devices against a

reference standard in a water bath, and 2) establish the most accurate of these four

devices to use as a comparative reference for the human investigation.

Findings

It was concluded in Chapter 3 that there were large limitations within the

current evidence base and it was unclear if devices were interchangeable in the

presence of external (e.g., exercise) or environmental stimuli (e.g., cold/heat

exposure).

In contrast to our null hypothesis in Chapter 4, clinically significant differences

were observed between infrared devices and the certified thermometer. In agreement

with the null hypothesis for Chapter 4, the thermistor was correctly identified as the

most accurate device compared to the certified thermometer in a water bath across

the expected physiological range, and was identified as the comparative device for

the subsequent 𝑇sk investigation (Chapter 5).

Findings of the 𝑇sk investigation suggest that even after calibration, conductive

and infrared devices are not interchangeable under resting, exercise or recovery

conditions for the measurement of 𝑇�sk. In addition, it should not be assumed that

devices within acceptable agreement during resting conditions will continue to agree

during exercise and recovery. In summary, the current findings demonstrate that

clinical and significant differences exist between conductive and infrared devices

96 Chapter 6: Conclusions

which are commonly employed in the assessment of human 𝑇sk in exercise science,

research and clinical settings.

Implications

These findings have important implications given the wide variety of

commercially available 𝑇sk measurement devices available to the public. Accurate

comparisons between publications using different 𝑇sk measurement methods may not

be possible under resting, exercise and high ambient conditions which elicit different

thermoregulatory responses. These significant differences between conductive and

infrared means could potentially influence the interpretation of results, diagnosis and

therefore treatment outcomes for clinical and exercise science applications.

Limitations

It should also be noted that only four types of devices were tested and our

findings might not be applicable to all the makes and models of skin measurement

instrumentation on the market. Calibration of conductive devices could have been

affected as the thermal conductivity and heat capacity of water is greater than that of

the human skin. Furthermore, during human testing (Chapter 5) only a portion of the

device is in contact with the skin, as opposed to being completely immersed in the

water bath (Chapter 4).

In regards to Chapter 5, due to the conductive devices being in direct contact

with the skin, comparisons made between devices were measured from sites adjacent

to each other and not a single point on the skin. Skin temperature variation within the

measurement area could contribute to measurement differences between devices.

However, this potential bias was diminished by randomly allocating devices within

the region of interest.

Future Research

Building upon the findings in Chapter 4, in order to determine if water vapour

influenced the calibration of infrared devices, it is recommended future studies

compare any potential differences in calibration formula for infrared devices derived

from both certified water baths and black body devices.

There is a lack of high quality investigations into the interchangeability of

commonly used skin temperature measurement devices. Moreover, the influence in

which interventions such as exercise or environmental stress has on measurement

Chapter 6: Conclusions 97

differences between devices has been largely ignored. Therefore, future research

should build upon the findings of the current study by assessing measurement

differences between devices during resting and exercise conditions (of differing

intensities and modalities) in a wider range of ambient temperatures (including cold

exposure). Further to this, greater understanding is required to determine whether

findings reported in this study can be applied to females, populations (young vs.

elderly; lean vs. obese) and/or ethnicities.

Appendices 99

Appendices

Appendix A Ethics Approval

100 Appendices

Appendix B Health Screen Questionnaire

Health Screen Questionnaire

Date / / Name

Sex Male Female D.O.B

Height Weight Resting Pulse

How are you feeling today? Well Unwell

Stage 1 - Medical Conditions

1. Have you in the past 18 months:

• Had any muscle or skeletal injuries No Yes

• Taken time off work due to injury No Yes

• Been nominated to light duties due to injury No Yes

If yes to any of the above, please provide details:

2. List any medications you take on a regular basis

3. Do you have diabetes? No Yes

a) If yes, please indicate if it is insulin dependent diabetes mellitus (IDDM) or non-insulin dependent diabetes mellitus (NIDDM). IDDM NIDDM

b) If IDDM, for how many years have you had IDDM? ___________years

4. Have you had a stroke? No Yes 5. Has your doctor ever said you have heart trouble? No Yes 6. Do you take asthma medication? No Yes 7. Is there any other physical reason that prevents you from participating

in a pre-employment physical activity program (e.g. cancer, osteoporosis, severe arthritis, mental illness, thyroid, kidney, or liver disease)?

No Yes

8. Do you have Raynaud’s phenomenon, thyroid disease, or any vascular disorders such as venous insufficiency or lower extremity arterial disease?

No Yes

Stage 2 – Signs and Symptoms

9. Do you often have pains in your heart, chest, or surrounding areas, especially during exercise?

No Yes

10. Do you often feel faint or have spells of severe dizziness during exercise?

No Yes

Appendices 101

11. Do you experience unusual fatigue or shortness of breath at rest or with mild exertion?

No Yes

12. Have you had an attack of shortness of breath that came on after you stopped exercising?

No Yes

13. Have you been awakened at night by an attack of shortness of breath? No Yes

14. Do you experience swelling or accumulation of fluid in or around your ankles?

No Yes

15. Do you often get the feeling that your heart is beating faster, racing, or skipping beats, either at rest or during exercise?

No Yes

16. Do you regularly get pains in your calves and lower legs during exercise that are not due to soreness or stiffness?

No Yes

17. Has your doctor ever told you that you have a heart murmur? No Yes Stage 3 - Cardiac Risk Factors

18. Do you smoke cigarettes on a daily basis, or have you quit smoking within the past two years?

No Yes

If yes, how many cigarettes per day do you smoke (or did you smoke in the past two years)? ___________per day

19. Has your doctor ever told you that you have high blood pressure? No Yes

20. Has your father, mother, brother, or sister had a heart attack or suffered from a cardiovascular disease before the age of 55?

No Yes

If yes,

a) Was the relative male or female? ___________

b) At what age did he or she suffer the stroke or heart attack? ___________

c) Did this person die suddenly as a result of the stroke or heart attack? ___________ 21. Do you know your:

a) Blood pressure? ___________mmHg

b) Cholesterol level? ___________mmol/L or mg/dL Stage 4 - Current Exercise

22. What are your current activity patterns?

a) Frequency: ___________exercise sessions per week

b) Intensity: Sedentary Moderate Vigorous

c) History: <3 months 3–12 months >12 months

d) Duration: ___________minutes per session 23. What types of exercises do you do?

102 Appendices

Appendix C Informed Consent

PARTICIPANT INFORMATION FOR QUT RESEARCH PROJECT

Interchangableability of contact and non-contact skin temperature devices

QUT Ethics Approval Number 1300000404 RESEARCH TEAM

Principal Researcher: Aaron Bach – Masters in Applied Science Student Associate Researcher: Ian Stewart – Associate Professor Associate Researcher: Joseph Costello – Postdoctoral Research Fellow Queensland University of Technology (QUT) DESCRIPTION

This project is being undertaken as part of a Masters study for Aaron Bach. The measurement of skin temperature has a wide range of applications that consist of – but are not limited to – exercise performance, the detection of overuse injuries, shock, heat strain, assessing burn and trauma injury, monitoring safe working practices and evaluating cryotherapy treatments. The primary methods of measuring skin temperature are derived from contact and non-contact devices. Each of these measures of skin temperature utilise different principles of thermal heat transfer. Contact methods are based upon thermal conduction between the skin and the measurement device. Popular contact measures include thermistors, thermocouples and iButtons with each device varying in specifications and performance. Non-contact measures – thermal imaging cameras and infrared thermometers – detect infrared energy being emitted from the skin. We have identified a gap in the literature where by few authors have considered the potential difference between contact and non-contact technologies. This oversight is particularly disconcerting in the management of workplace safety, exercise performance and clinical diagnosis – where considerable changes in the technology, particularly thermal imaging cameras, have occurred. The purpose of this research is to identify the current ‘gold standard’ in skin temperature measurement during resting and exercise conditions. To do this 4 devices will be used; 2 contact – thermistor and iButton – and 2 non-contact – infrared camera and infrared thermometer.

a) Wired Thermistor; b) Wireless iButton; c) Infrared Thermometer; d) Infrared Camera.

PARTICIPATION

Testing will involve measuring your skin temperature with the 4 different (non-invasive) devices during rest, exercise and recovery.

• On arrival your skin fold measurements will then be taken to determine your body fat percentage.

• Following that you will have four regions of interest cleaned and marked – 1. Back of your neck, 2. RIGHT shoulder blade, 3. Back of your LEFT hand & 4. The WHOLE front of your RIGHT shin.

a) b) c) d)

http://www.qut.edu.au/

Appendices 103

• All testing will take place in a temperature controlled room (where you will be able to watch movies while you are seated). 1. After a 20 minute seated adjustment period, you will sit passively for a further 30

minutes for the resting measurement period (room temperature = 24 °C). 2. You will then enter an environmental chamber (room temperature = 38 °C) where you

will cycle for 30 minutes at 60 rpm (with a 2.0 kg weighted basket). 3. You will then return to the 24 °C room and remain seated for a further 45 minute

recording period. Skin temperature will be taken with the two independent contact measures (wireless iButton and wired Thermocouple) adhered to each site with sports tape. Two other non-invasive, non-contact devices will be used to measure skin temperature at the same sites. The first is an infrared thermometer, which a research member will hold above the surface of your skin to take an instant skin temperature measurement. The second is an infrared camera, this camera will be used to take still images of four skin sites to analyse skin temperature. The infrared camera will be set up on a tripod in front of you when measurements are required and taking the photo is exactly the same as a traditional camera. It should be known that skin temperature measurements taken with the infrared camera are done so by taking non-identifiable still images of your skin. Heart rate, core body temperature and rating of perceived exertion will also be monitored throughout any exercise undertaken in this study. Your participation in this project is entirely voluntary. • To ensure accurate measurements from the camera we ask you avoid prolonged sun exposure

five days prior to the testing day (to prevent sunburn). • All sites will be need to be free of hair, so if appropriate, please shave the areas shown (Figure

1) no closer than 36hours before testing. This prevents inflammation or damage to the skin surface from shaving influencing skin temperature values.

• If you are testing in the morning eat a normal breakfast with 500mL of water before arriving to the lab. If you are testing in the afternoon then eat a normal lunch with 500mL of water before arriving to the lab.

• On the day of testing please keep the sites (Figure 1) clean of make-up, topical agents, creams etc; not to engage in vigorous exercise, ingest caffeine or alcohol. Also do not have a hot shower within two hours of testing (e.g. no later than 8am, if testing at 10am).

• Clothing needs to be unencumbering and conducive to exercise (i.e. runners, socks, shorts and a t-shirt). There are showers, change rooms and toilets for you after if you wish to bring a change of clothes.

• Bring a water bottle, and food if you wish (there is a kitchen next door to reheat any food). • Testing will take approximately 3-4hours. Your decision to participate or not participate will in no way impact upon your current or future relationship with QUT (for example your grades). If you do agree to participate you can withdraw from the project at any time without comment or penalty. Any identifiable information already obtained from you will be destroyed.

Figure 1. Areas that need shaving no closer than 36 hours before testing.

e.g. if you have testing on a Wednesday morning, shave no later than Monday night before bed.

104 Appendices

EXPECTED BENEFITS

It is expected that this project will not benefit you directly. However, by participating in this research you will be helping to determine the difference between contact and non-contact forms of skin temperature measures. This could have valuable applications in sporting, clinical and occupational settings; through greater understanding of physiological relationships between the skin during exercise, the diagnosis of thermal skin conditions (e.g. pressure ulcers) and workplace safety standards (e.g. mining).

To compensate you for your contribution, should you choose to participate, the research team will provide you with a report of your individual results of body characteristics (ie. body fat percentage and Body Mass Index (BMI)).

RISKS

There are minimal risks associated with your participation in this project. All exercise testing has the potential for complications such as fatigue, muscle soreness, irregular heartbeat, chest pain and rarely heart attack. This risk will be minimised through health screening, prior to the commencement of testing. To minimize these risks further you will have a trained exercise scientist supervising all testing. In addition, you will have your heart rate and rate of perceived exertion monitored continuously during any exercise. The exercise will be discontinued if any abnormal heart rate or rhythm is detected with immediate medical attention sought. All exercise within this study will take place on an exercise bike which is a safer testing modality than a treadmill. Exercise also has the potential to lead to heat illness, although would not be expected in this study with moderate intensity exercise. Nevertheless, you will be informed of the signs and symptoms of heat illness, and encouraged to stop exercising if you experience them. A trained exercise scientist will also stop the test if signs and symptoms of heat illness are present. Core body temperature will be monitored continuously throughout the exercise tests, and is a gold standard indicator of heat illness. If core temperature reaches 39 degrees Celsius the test will be terminated. This cut off limit is in-line with the recommendations of the International Organisation for Standardisation (ISO 9886: 2004). Should the test be terminated due to symptoms of heat illness or reaching the core body temperature limit, you will be moved from the bike and onto a mat. Cooling procedures including rest, sips of cool water, fanning, and removal of excess clothing will be initiated. Should the test be terminated due to any complications immediate medical attention will be sought. This will be done by calling for an ambulance and alerting QUT security. Attachment of contact devices to the skin requires adhesive tape. This could potentially be an allergen to yourself and will be asked of in pre-testing screening. Low allogeneic tape will be used to help minimise any reactions if you are not aware of a prior adhesive allergy. If an allergy occurs we will document the incident and notify a doctor that of the reaction and send you to get medical treatment and evaluation. The risks present in the current investigation will be monitored and controlled. This research has the potential to lead to improved field tests for skin temperature assessment and as a result increase safety in sporting, occupational, research and clinical settings. PRIVACY AND CONFIDENTIALITY

Any data collected (including images) as part of this project will be stored securely as per QUT’s Management of research data policy i.e., All information provided to or collected by the research team will be treated confidentially. Individuals will not be identified in any papers reporting the findings of the present investigation. Please note that non-identifiable data collected in this project may be used as comparative data in future projects.

CONSENT TO PARTICIPATE

We would like to ask you to sign a written consent form (enclosed) to confirm your agreement to participate. Images taken with the infrared camera will be used for data collection in the study and

Appendices 105

have the potential to be used for journal publications, conference presentations and teaching materials. It is not expected that you will be identifiable due to the close proximity the images will be taken and the output of the image displays your skin in various colours that represent a given temperature. Should the images be identifiable, measures will be taken to ensure anonymity (i.e. covering identifiable facial features).

QUESTIONS / FURTHER INFORMATION ABOUT THE PROJECT

If have any questions or require further information please contact one of the research team members below.

Aaron Bach Ian Stewart Joseph Costello School of Exercise & Nutrition Sciences

Institute of Health & Biomedical Innovation

School of Exercise & Nutrition Sciences

07 3138 8296 07 3138 6118 07 3138 4168 [email protected] [email protected] [email protected]

CONCERNS / COMPLAINTS REGARDING THE CONDUCT OF THE PROJECT

QUT is committed to research integrity and the ethical conduct of research projects. However, if you do have any concerns or complaints about the ethical conduct of the project you may contact the QUT Research Ethics Unit on 07 3138 5123 or email [email protected]. The QUT Research Ethics Unit is not connected with the research project and can facilitate a resolution to your concern in an impartial manner.

Thank you for helping with this research project. Please keep this sheet for your information.

mailto:[email protected]




Appendices 106

Appendix D Complete graphed data for mean skin temperature and all individual sites

Figure D1. Mean skin temperature (MTSK) of all tested devices during rest (4 devices), exercise (3 devices) and recovery (4 devices). TM: Thermistor; IB: iButton®; IT: Infrared Thermometer; IC: Infrared Camera.

Appendices 107

Figure

D2. Neck skin

temperature of all tested devices during rest (4 devices), exercise (3 devices) and recovery (4 devices). TM: Thermistor; IB: iButton®; IT: Infrared Thermometer; IC: Infrared Camera

Appendices 108

Figure D3. Scapula skin temperature of all tested devices during rest (4 devices), exercise (3 devices) and recovery (4 devices). TM: Thermistor; IB: iButton®; IT: Infrared Thermometer; IC: Infrared Camera.

Appendices 109

Figure D4. Hand skin temperature of all tested devices during rest (4 devices), exercise (3 devices) and recovery (4 devices). TM: Thermistor; IB: iButton®; IT: Infrared Thermometer; IC: Infrared Camera.

Appendices 110

Figure D5. Shin skin temperature of all tested devices during rest (4 devices), exercise (3 devices) and recovery (4 devices). TM: Thermistor; IB: iButton®; IT: Infrared Thermometer; IC: Infrared Camera.

Appendices 111

Appendix E Complete ANOVA outputs for all sites and conditions

Thermoneutral (Neck) Not Normally Distributed (Greenhouse-Geisser) Within Subjects:

Device Time Device * Time F3, 87 =56.188 F10, 290 = 0.821 F30, 870 = 1.809 P<0.001 P = 0.442 P = 0.047 1 - β = 1.00 1 - β = 0.182 1 - β = 0.882

Pairwise Comparisons: Mean Diff (Devices)

95% CI

Devices Mean Diff Sig. Lower Upper

TM : IB -0.212 0.06 -0.378 -0.047

TM : IT -0.479 <0.001 -0.73 -0.227

TM : IC -0.931 <0.001 -1.184 -0.678

IB : IT -0.266 0.004 -0.463 -0.069

IB : IC -0.719 <0.001 -0.926 -0.511

IT : IC -0.452 <0.001 -0.65 -0.255

Thermoneutral (Scap) Not Normally Distributed (Greenhouse-Geisser) Within Subjects:

Device Time Device * Time F3, 87 = 57.664 F10, 290 = 1.923 F30, 870 = 1.319 P<0.001 P = 0.140 P = 0.231 1 - β = 1.00 1 - β = 0.449 1 - β = 0.618


95% CI


TM : IB -0.136 0.089 -0.285 0.013

TM : IT -0.335 <0.001 -0.539 -0.132

TM : IC -0.901 <0.001 -1.164 -0.639

IB : IT -0.199 0.016 -0.371 -0.027

IB : IC -0.765 <0.001 -1.008 -0.523

IT : IC -0.566 <0.001 -0.77 -0.362

Thermoneutral (Hand) Normally Distributed (Sphericity Assumed) Within Subjects:

Device Time Device * Time F3, 87 =32.747 F10, 290 = 58.156 F30, 870 = 1.220 P<0.001 P<0.001 P = 0.194 1 - β = 1.00 1 - β = 1.00 1 - β = 0.951


95% CI


TM : IB -0.064 1.000 -0.326 -0.197

TM : IT -0.249 0.016 -0.464 -0.035

TM : IC -0.867 <0.001 -1.181 -0.554

IB : IT -0.185 0.324 -0.446 -0.076

IB : IC -0.803 <0.001 -1.169 -0.437

IT : IC -0.618 <0.001 -0.831 -0.405

112 Appendices

Thermoneutral (Shin) Not Normally Distributed (Greenhouse-Geisser) Within Subjects:

Device Time Device * Time F3, 87 =46.130 F10, 290 = 24.342 F30, 870 = 1.462 P<0.001 P<0.001 P = 0.196 1 - β = 1.00 1 - β = 1.00 1 - β = 0.550


95% CI


TM : IB 0.338 0.002 -0.378 -0.047

TM : IT -0.252 0.002 -0.73 -0.227

TM : IC -0.661 <0.001 -1.184 -0.678

IB : IT -0.590 <0.001 -0.463 -0.069

IB : IC -0.999 <0.001 -0.926 -0.511

IT : IC -0.410 <0.001 -0.65 -0.255 Thermoneutral (MTSK) Not Normally Distributed (Greenhouse-Geisser) Within Subjects:

Device Time Device * Time F3, 87 = 103.773 F10, 290 = 5.687 F30, 870 = 2.734 P<0.001 P = 0.008 P = 0.004 1 - β = 1.00 1 - β = 0.802 1 - β = 0.960


95% CI


TM : IB -0.013 1.000 -0.113 0.087

TM : IT -0.339 <0.001 -0.447 -0.231

TM : IC -0.834 <0.001 -1.031 -0.638

IB : IT -0.326 <0.001 -0.433 -0.219

IB : IC -0.821 <0.001 -1.020 -0.623

IT : IC -0.495 <0.001 -0.670 -0.320

Exercise (Neck) Not Normally Distributed (Greenhouse-Geisser) Within Subjects:

Device Time Device * Time F2, 58 = 58.750 F10, 290 = 71.581 F20, 580 = 77.915 P<0.001 P<0.001 P<0.001 1 - β = 1.00 1 - β = 1.00 1 - β = 1.00


95% CI


TM:IB -0.196 0.001 -0.314 -0.078

TM:IRT 0.429 <0.001 0.247 0.661

IB:IRT 0.625 <0.001 0.482 0.768

Appendices 113

Exercise (Scap) Not Normally Distributed (Greenhouse-Geisser) Within Subjects:



95% CI


TM:IB -0.270 <0.001 -0.385 -0.155

TM:IRT 0.450 <0.001 0.263 0.637

IB:IRT 0.720 <0.001 0.572 0.868 Exercise (Hand) Normally Distributed (Sphericity Assumed) Within Subjects:



95% CI


TM:IB -0.188 0.061 -0.382 0.007

TM:IRT 0.298 0.001 0.115 0.482

IB:IRT 0.486 <0.001 0.284 0.688 Exercise (Shin) Not Normally Distributed (Greenhouse-Geisser) Within Subjects:



95% CI


TM:IB -0.331 0.001 -0.539 -0.123

TM:IRT 0.592 <0.001 0.360 0.824

IB:IRT 0.923 <0.001 0.617 1.229

114 Appendices

Exercise (MTSK) Not Normally Distributed (Greenhouse-Geisser) Within Subjects:



95% CI


TM:IB -0.253 <0.001 -0.335 -0.172

TM:IRT 0.460 <0.001 0.339 0.581

IB:IRT 0.713 <0.001 0.606 0.821

Recovery (Neck) Not Normally Distributed (Greenhouse-Geisser) Within Subjects:

Device Time Device * Time F3, 87 =102.988 F10, 290 = 80.111 F30, 870 = 97.880 P<0.001 P<0.001 P<0.001 1 - β = 1.00 1 - β = 1.00 1 - β = 1.00


95% CI


TM : IB -0.360 0.047 -0.717 -0.003

TM : IT -1.423 <0.001 -1.834 -1.013

TM : IC -2.232 <0.001 -2.720 -1.744

IB : IT -1.064 <0.001 -1.466 -0.662

IB : IC -1.873 <0.001 -2.334 -1.411

IT : IC -0.809 <0.001 -1.053 -0.565 Recovery (Scap) Not Normally Distributed (Greenhouse-Geisser) Within Subjects:

Device Time Device * Time F3, 87 =100.922 F10, 290 = 83.283 F30, 870 = 59.846 P<0.001 P<0.001 P<0.001 1 - β = 1.00 1 - β = 1.00 1 - β = 1.00


95% CI


TM : IB -0.508 <0.001 -0.723 -0.293

TM : IT -1.250 <0.001 -1.655 -0.845

TM : IC -2.047 <0.001 -2.469 -1.625

IB : IT -0.743 <0.001 -1.143 -0.343

IB : IC -1.539 <0.001 -1.950 -1.128

IT : IC -0.796 <0.001 -1.002 -0.590

Appendices 115

Recovery (Hand) Not Normally Distributed (Greenhouse-Geisser) Within Subjects:



95% CI


TM : IB -0.524 0.001 -0.872 -0.177

TM : IT -1.007 <0.001 -1.316 -0.699

TM : IC -1.992 <0.001 -2.446 -1.538

IB : IT -0.483 0.006 -0.856 -0.110

IB : IC -1.467 <0.001 -1.949 -0.985

IT : IC -0.984 <0.001 -1.333 -0.636 Recovery (Shin) Normally Distributed (Sphericity Assumed) Within Subjects:



95% CI


TM : IB -0.143 1.000 -0.443 0.157

TM : IT -0.476 <0.001 -0.729 -0.224

TM : IC -1.288 <0.001 -1.672 -0.904

IB : IT -0.333 0.011 -0.608 -0.059

IB : IC -1.145 <0.001 -1.556 -0.735

IT : IC -0.812 <0.001 -1.064 -0.560 Recovery (MTSK) Normally Distributed (Sphericity Assumed) Within Subjects:



95% CI


TM : IB -0.367 <0.001 -0.530 -0.203

TM : IT -1.041 <0.001 -1.263 -0.819

TM : IC -1.880 <0.001 -2.194 -1.567

IB : IT -0.674 <0.001 -0.912 -0.436

IB : IC -1.514 <0.001 -1.828 -1.199

IT : IC -0.840 <0.001 -1.034 -0.645

116 Appendices

Appendix F Complete post-hoc paired sample T-test comparisons between all devices

RESTING: TIME POINT 1 Paired Samples Test

Paired Differences t

df

Sig. (2-tailed)

Mean

SD

Std. Error

Mean

95% Confidence Interval of the Difference

Lower Upper Pair 1 TM6 - IB6 -.03833 .17473 .03190 -.10358 .02691 -1.202 29 .239 Pair 2 TM6 - IT6 -.40500 .24387 .04452 -.49606 -.31394 -9.096 29 .000 Pair 3 TM6 - IC6 -.82500 .41931 .07655 -.98157 -.66843 -10.777 29 .000 Pair 4 IB6 - IT6 -.36667 .25444 .04645 -.46168 -.27166 -7.893 29 .000 Pair 5 IB6 - IC6 -.78667 .42367 .07735 -.94487 -.62846 -10.170 29 .000 Pair 6 IT6 - IC6 -.42000 .34780 .06350 -.54987 -.29013 -6.614 29 .000



df

Sig. (2-tailed)

Mean

SD

Std. Error

Mean


Lower Upper Pair 1 TM6 - IB6 -.00433 .20056 .03662 -.07922 .07056 -.118 29 .907 Pair 2 TM6 - IT6 -.35200 .21640 .03951 -.43281 -.27119 -8.909 29 .000 Pair 3 TM6 - IC6 -.85200 .40954 .07477 -1.00493 -.69907 -11.395 29 .000 Pair 4 IB6 - IT6 -.34767 .22758 .04155 -.43265 -.26269 -8.368 29 .000 Pair 5 IB6 - IC6 -.84767 .40463 .07387 -.99876 -.69658 -11.474 29 .000 Pair 6 IT6 - IC6 -.50000 .35912 .06557 -.63410 -.36590 -7.626 29 .000



df

Sig. (2-tailed)

Mean

SD

Std. Error

Mean


Lower Upper Pair 1 TM11 - IB11 -.01633 .20934 .03822 -.09450 .06184 -.427 29 .672 Pair 2 TM11 - IT11 -.30633 .22590 .04124 -.39069 -.22198 -7.427 29 .000 Pair 3 TM11 - IC11 -.82967 .41824 .07636 -.98584 -.67350 -10.865 29 .000 Pair 4 IB11 - IT11 -.29000 .22273 .04066 -.37317 -.20683 -7.132 29 .000 Pair 5 IB11 - IC11 -.81333 .40276 .07353 -.96373 -.66294 -11.061 29 .000 Pair 6 IT11 - IC11 -.52333 .37295 .06809 -.66260 -.38407 -7.686 29 .000

EXERCISE: TIME POINT 1 Paired Samples Test


df

Sig. (2-tailed)

Mean

SD

Std. Error

Mean


Lower Upper Pair 1 TM1 - IB1 .56033 .25957 .04739 .46341 .65726 11.824 29 .000 Pair 2 TM1 - IT1 -.84333 .36812 .06721 -.98079 -.70587 -12.548 29 .000 Pair 3 IB1 - IT1 -1.40367 .42796 .07813 -1.56347 -1.24386 -17.965 29 .000

Appendices 117



df

Sig. (2-tailed)

Mean

SD

Std. Error

Mean


Lower Upper Pair 1 TM3 - IB3 -.02567 .18207 .03324 -.09365 .04232 -.772 29 .446 Pair 2 TM3 - IT3 .31767 .47157 .08610 .14158 .49375 3.690 29 .001 Pair 3 IB3 - IT3 .34333 .53107 .09696 .14503 .54164 3.541 29 .001



df

Sig. (2-tailed)

Mean

SD

Std. Error

Mean


Lower Upper Pair 1 TM5 - IB5 -.26900 .19691 .03595 -.34253 -.19547 -7.482 29 .000 Pair 2 TM5 - IT5 .88333 .30942 .05649 .76779 .99887 15.636 29 .000 Pair 3 IB5 - IT5 1.15233 .28459 .05196 1.04607 1.25860 22.178 29 .000



df

Sig. (2-tailed)

Mean

SD

Std. Error

Mean





df

Sig. (2-tailed)

Mean

SD

Std. Error

Mean





df

Sig. (2-tailed)

Mean

SD

Std. Error

Mean


Lower Upper

Pair 1 TM11 - IB11 -.56633 .28089 .05128 -.67122 -.46145 -11.043 29 .000 Pair 2 TM11 - IT11 .46000 .40085 .07319 .31032 .60968 6.285 29 .000 Pair 3 IB11 - IT11 1.02633 .43068 .07863 .86551 1.18715 13.052 29 .000

118 Appendices

RECOVERY: TIME POINT 1 Paired Samples Test


df

Sig. (2-tailed)

Mean

SD

Std. Error Mean


Lower Upper

Pair 1 TM1 - IB1 -1.04833 .37850 .06910 -1.18967 -.90700 -15.170 29 .000 Pair 2 TM1 - IT1 .91500 .32953 .06016 .79195 1.03805 15.208 29 .000 Pair 3 TM1 - IC1 -.14167 .42099 .07686 -.29887 .01553 -1.843 29 .076 Pair 4 IB1 - IT1 1.96333 .53700 .09804 1.76281 2.16385 20.025 29 .000 Pair 5 IB1 - IC1 .90667 .58539 .10688 .68808 1.12525 8.483 29 .000 Pair 6 IT1 - IC1 -1.05667 .35689 .06516 -1.18993 -.92340 -16.217 29 .000



df

Sig. (2-tailed)

Mean

SD

Std. Error

Mean


Lower Upper Pair 1 TM3 - IB3 -.78633 .41649 .07604 -.94185 -.63081 -10.341 29 .000 Pair 2 TM3 - IT3 -.68133 .70501 .12872 -.94459 -.41808 -5.293 29 .000 Pair 3 TM3 - IC3 -1.67133 .71143 .12989 -1.93699 -1.40568 -12.867 29 .000 Pair 4 IB3 - IT3 .10500 .67656 .12352 -.14763 .35763 .850 29 .402 Pair 5 IB3 - IC3 -.88500 .69064 .12609 -1.14289 -.62711 -7.019 29 .000 Pair 6 IT3 - IC3 -.99000 .42778 .07810 -1.14974 -.83026 -12.676 29 .000



df

Sig. (2-tailed)

Mean

SD

Std. Error

Mean


Lower Upper Pair 1 TM5 - IB5 -.57200 .40761 .07442 -.72420 -.41980 -7.686 29 .000 Pair 2 TM5 - IT5 -1.41200 .63361 .11568 -1.64859 -1.17541 -12.206 29 .000 Pair 3 TM5 - IC5 -2.36200 .79389 .14494 -2.65844 -2.06556 -16.296 29 .000 Pair 4 IB5 - IT5 -.84000 .64571 .11789 -1.08111 -.59889 -7.125 29 .000 Pair 5 IB5 - IC5 -1.79000 .77939 .14230 -2.08103 -1.49897 -12.579 29 .000 Pair 6 IT5 - IC5 -.95000 .39018 .07124 -1.09570 -.80430 -13.336 29 .000



df

Sig. (2-tailed)

Mean

SD

Std. Error

Mean


Lower Upper Pair 1 TM7 - IB7 -.39067 .37203 .06792 -.52959 -.25175 -5.752 29 .000 Pair 2 TM7 - IT7 -1.57267 .64407 .11759 -1.81317 -1.33217 -13.374 29 .000 Pair 3 TM7 - IC7 -2.43267 .81105 .14808 -2.73552 -2.12981 -16.428 29 .000 Pair 4 IB7 - IT7 -1.18200 .58924 .10758 -1.40203 -.96197 -10.987 29 .000 Pair 5 IB7 - IC7 -2.04200 .73798 .13474 -2.31757 -1.76643 -15.156 29 .000 Pair 6 IT7 - IC7 -.86000 .39966 .07297 -1.00923 -.71077 -11.786 29 .000

Appendices 119



df

Sig. (2-tailed)

Mean

SD

Std. Error

Mean


Lower Upper Pair 1 TM9 - IB9 -.22967 .33020 .06029 -.35296 -.10637 -3.810 29 .001 Pair 2 TM9 - IT9 -1.56567 .61919 .11305 -1.79687 -1.33446 -13.850 29 .000 Pair 3 TM9 - IC9 -2.33233 .78754 .14378 -2.62641 -2.03826 -16.221 29 .000 Pair 4 IB9 - IT9 -1.33600 .57647 .10525 -1.55126 -1.12074 -12.694 29 .000 Pair 5 IB9 - IC9 -2.10267 .73868 .13486 -2.37850 -1.82684 -15.591 29 .000 Pair 6 IT9 - IC9 -.76667 .40797 .07448 -.91900 -.61433 -10.293 29 .000


Paired Differences

t df Sig. (2-tailed) Mean

Std. Deviatio

n

Std. Error Mean


Lower Upper Pair 1 TM11 - IB11 -.10433 .33236 .06068 -.22844 .01977 -1.719 29 .096 Pair 2 TM11 - IT11 -1.39200 .59198 .10808 -1.61305 -1.17095 -12.879 29 .000 Pair 3 TM11 - IC11 -2.09867 .77252 .14104 -2.38713 -1.81020 -14.880 29 .000 Pair 4 IB11 - IT11 -1.28767 .56843 .10378 -1.49992 -1.07541 -12.408 29 .000 Pair 5 IB11 - IC11 -1.99433 .71118 .12984 -2.25989 -1.72877 -15.359 29 .000 Pair 6 IT11 - IC11 -.70667 .39994 .07302 -.85601 -.55733 -9.678 29 .000


Paired Differences t df Sig. (2-tailed) Mean Std.

Deviation

Std. Error Mean


Lower Upper Pair 1 TM13 - IB13 .01067 .34506 .06300 -.11818 .13952 .169 29 .867 Pair 2 TM13 - IT13 -1.12033 .50539 .09227 -1.30905 -.93162 -12.142 29 .000 Pair 3 TM13 - IC13 -1.81700 .66392 .12121 -2.06491 -1.56909 -14.990 29 .000 Pair 4 IB13 - IT13 -1.13100 .51541 .09410 -1.32346 -.93854 -12.019 29 .000 Pair 5 IB13 - IC13 -1.82767 .64326 .11744 -2.06786 -1.58747 -15.562 29 .000 Pair 6 IT13 - IC13 -.69667 .43667 .07972 -.85972 -.53361 -8.738 29 .000


Paired Differences t df Sig. (2-tailed) Mean Std.

Deviation

Std. Error Mean


Lower Upper Pair 1 TM15 - IB15 .08933 .34195 .06243 -.03835 .21702 1.431 29 .163 Pair 2 TM15 - IT15 -.86467 .39044 .07128 -1.01046 -.71887 -12.130 29 .000 Pair 3 TM15 - IC15 -1.54467 .59057 .10782 -1.76519 -1.32414 -14.326 29 .000 Pair 4 IB15 - IT15 -.95400 .46458 .08482 -1.12748 -.78052 -11.247 29 .000 Pair 5 IB15 - IC15 -1.63400 .61274 .11187 -1.86280 -1.40520 -14.606 29 .000 Pair 6 IT15 - IC15 -.68000 .41473 .07572 -.83486 -.52514 -8.981 29 .000

References 121

References

Al-Nakhli, H., J, P., Laymon, M., & Berk, L. (2012). The use of thermal infra-red

imaging to detect delayed onset muscle soreness. Journal of Visualized

Experiments, 1(59), e3551/1-9.

Al-Nakhli, H., Petrofsky, J., Laymon, M., Arai, D., Holland, K., & Berk, L. (2012).

The use of thermal infrared imaging to assess the efficacy of a therapeutic

exercise program in individuals with diabetes. Diabetes Technology &

Therapeutics, 14(2), 159-167.

Aldemir, H., Atkinson, G., Cable, T., Edwards, B., Waterhouse, J., & Reilly, T.

(2000). A comparison of the immediate effects of moderate exercise in the early

morning and late afternoon on core temperature and cutaneous thermoregulatory

mechanisms. Chronobiology International, 17(2), 197-207.

Ammer, K. (2003). Need for standardisation of measurements in thermal imaging. In

B. Wiecek (Ed.), Thermography and lasers in medicine (pp. 13-17). Wólczańska:

Łódź.

Ammer, K. (2008). The glamorgan protocol for recording and evaluation of thermal

images of the human body. Thermology International, 18(4), 125-144.

Ammer, K. (2009). Cold challenge to provoke a vasospastic reaction in fingers

determined by temperature measurements; a systematic review. Thermology

International, 19(4), 109-118.

Ammer, K. (2012). Temperature of the human knee - a review. Thermology

International, 22(4), 137-151.

Ammer, K., Melnizky, P., & Rathkolb, O. (2003). Skin temperature after intake of

sparkling wine, still wine or sparkling water. Thermology International, 13(3),

99-102.

Ammer, K., & Ring, E. (2005). Influence of the field of view on temperature

readings from thermal images. Thermology International, 15(3), 99-103.

122 References

Ammer, K., & Ring, E. (2006). Standard procedures for infrared imaging in

medicine. Boca Raton: CRC Press.

Anbar, M. (2002). Assessment of physiologic and pathologic radiative heat

dissipation using dynamic infrared imaging. Annals of the New York Academy of

Sciences, 972(1), 111-118.

Arciero, P.J., Goran, M.I., & Poehlman, E.T. (1993). Resting metabolic rate is lower

in women than in men. Journal of Applied Physiology, 75(6), 2514-2520.

Armstrong, D., Lavery, L., Liswood, P., Todd, W., & Tredwell, J. (1997). Infrared

dermal thermometry for the high-risk diabetic foot. Physical Therapy, 77(2), 169-

175.

Armstrong, L., & Maresh, C. (1993). The exertional heat illnesses: A risk of athletic

participation. Medicine Exercise Nutrition and Health, 2(3), 125-147.

Arnett, M. (2002). Effects of prolonged and reduced warm-ups on diurnal variation

in body temperature and swim performance. The Journal of Strength &

Conditioning Research, 16(2), 256-261.

Arora, N., Martins, D., Ruggerio, D., Tousimis, E., Swistel, A.J., Osborne, M.P., &

Simmons, R.M. (2008). Effectiveness of a noninvasive digital infrared thermal

imaging system in the detection of breast cancer. The American Journal of

Surgery, 196(4), 523-526.

ASTM-E1965. (1998). Standard specification for infrared thermometers for

intermittent determination of patient temperature. Pennsylvania: Annual book of

ASTM Standards.

Atkins, P. (2010). The laws of thermodynamics: A very short introduction. New

York: Oxford University Press.

Baker, F., & Driver, H.S. (2007). Circadian rhythms, sleep, and the menstrual cycle.

Sleep Medicine, 8(6), 613-622.

Baker, P., & Daniels, F. (1956). Relationship between skinfold thickness and body

cooling for two hours at 15 c. Journal of Applied Physiology, 8(4), 409-416.

Bartelink, M., Wollersheim, H., Theeuwes, A., Van Duren, D., & Thien, T. (1990).

Changes in skin blood flow during the menstrual cycle: The influence of the

References 123

menstrual cycle on the peripheral circulation in healthy female volunteers.

Clinical Science, 78(5), 527-532.

Ben-Eliyahu, D. (1991). Infrared thermographic imaging in the detection of

sympathetic dysfunction in patients with patellofemoral pain syndrome. Journal

of manipulative and physiological therapeutics, 15(3), 164-170.

Bernard, V., Staffa, E., Mornstein, V., & Bourek, A. (2013). Infrared camera

assessment of skin surface temperature- effect of emissivity. Physica Medica,

29(6), 583-91.

Binkley, H.M., Beckett, J., Casa, D.J., Kleiner, D.M., & Plummer, P.E. (2002).

National athletic trainers' association position statement: Exertional heat

illnesses. Journal of Athletic Training, 37(3), 329-343.

Bitar, D., Goubar, A., & Desenclos, J.C. (2009). International travels and fever

screening during epidemics: A literature review on the effectiveness and potential

use of non-contact infrared thermometers. Eurosurveillance, 14(6), 1-5.

Bittel, J., & Henane, R. (1975). Comparison of thermal exchanges in men and

women under neutral and hot conditions. The Journal of Physiology, 250(3), 475-

489.

Bland, J., & Altman, D. (1986). Statistical methods for assessing agreement between

two methods of clinical measurement. The lancet, 327(8476), 307-310.

Blatteis, C., Boulant, J., Cabanac, M., Cannon, B., Freedman, R., Gordon, C., . . .

Kozyreva, T. (2001). Glossary of terms for thermal physiology. Japanese

Journal of Physiology, 51(2), 245-280.

Bland, J., & Altman, D. (1995). Comparing methods of measurement: why plotting

difference against standard method is misleading. The Lancet, 346(8982), 1085-

1087.

Bleakley, C., Costello, J.T., & Glasgow, P.D. (2012). Should athletes return to sport

after applying ice? Sports Medicine, 42(1), 69-87.

Bleakley, C., & Hopkins, J. (2010). Is it possible to achieve optimal levels of tissue

cooling in cryotherapy? Physical Therapy Reviews, 15(4), 344-350.

124 References

Boetcher, S., Sparrowb, E., & Dugay, M. (2009). Characteristics of direct-contact,

skin-surface temperature sensors. International Journal of Heat and Mass

Transfer, 52(15), 3799-3804.

Bouchama, A., & Knochel, J.P. (2002). Heat stroke. New England Journal of

Medicine, 346(25), 1978-1988.

Bourlai, T., Pryor, R., Suyama, J., Reis, S., & Hostler, D. (2012). Use of thermal

imagery for estimation of core body temperature during precooling, exertion, and

recovery in wildland firefighter protective clothing. Prehospital Emergency

Care, 16(3), 390-399.

Bouzida, N., Bendada, A., & Maldague, X.P. (2009). Visualization of body

thermoregulation by infrared imaging. Journal of Thermal Biology, 34(3), 120-

126.

Boylan, A., Martin, C., & Gardner, G. (1992). Infrared emissivity of burn wounds.

Clinical Physics and Physiological Measurement, 13(2), 125-127.

Brajkovic, D., & Ducharme, M. (2003). Finger dexterity, skin temperature, and blood

flow during auxiliary heating in the cold. Journal of Applied Physiology, 95(2),

758-770.

Brajkovic, D., Ducharme, M., & Frim, J. (2001). Relationship between body heat

content and finger temperature during cold exposure. Journal of Applied

Physiology, 90(6), 2445-2452.

Brake, D., & Bates, G. (2003). Fluid losses and hydration status of industrial workers

under thermal stress working extended shifts. Occupational and Environmental

Medicine, 60(2), 90-96.

Brake, D., & Bates, G.P. (2002). Limiting metabolic rate (thermal work limit) as an

index of thermal stress. Applied Occupational and Environmental Hygiene,

17(3), 176-186.

Brooks, E., Morgan, A., Pierzga, J., Wladkowski, S., O’Gorman, J., Derr, J., &

Kenney, W. (1997). Chronic hormone replacement therapy alters

thermoregulatory and vasomotor function in postmenopausal women. Journal of

Applied Physiology, 83(2), 477-484.

References 125

Buono, M., Jechort, A., Marques, R., Smith, C., & Welch, J. (2007). Comparison of

infrared versus contact thermometry or measuring skin temperature during

exercise in the heat. Physiological Measurement, 28(8), 855-859.

Buono, M., & Ulrich, R. (1998). Comparison of mean skin temperature using

'covered' versus 'uncovered'contact thermistors. Physiological Measurement,

19(2), 297-300.

Burnham, R.S., McKinely, R.S., & Vincent, D.D. (2006). Three types of skin-surface

termometers: A comparison of reliability, validity and responsiveness. American

Journal of Physical Medicine & Rehabilitation, 85(7), 553-558.

Burstein, R., Cliffer, K.D., & Giesler, G. (1987). Direct somatosensory projections

from the spinal cord to the hypothalamus and telencephalon. The Journal of

Neuroscience, 7(12), 4159-4164.

Burton, A.C. (1934). A new technique for the measurement of average skin

temperature over surfaces of the body and changes in skin temperature during

exercise. The Journal of Nutrition, 7(5), 481-496.

Burton, A.C. (1935). Human calorimetry ii. The average temperature of the tissues of

the body three figures. The Journal of Nutrition, 9(3), 261-280.

Cabanac, M. (1975). Temperature regulation. Annual Review of Physiology, 37(1),

415-439.

Carter III, R., Cheuvront, S.N., Williams, J.O., Kolka, M.A., Stephenson, L.A.,

Sawka, M.N., & Amoroso, P.J. (2005). Epidemiology of hospitalizations and

deaths from heat illness in soldiers. Army Research Institute Of Environmental

Medicine Natick Ma Thermal And Mountain Medicine Division, 4-24.

Casa, D., Becker, S., Ganio, M., Brown, C., Yeargin, S., Roti, M., . . . Maresh, C.

(2007). Validity of devices that assess body temperature during outdoor exercise

in the heat. Journal of Athletic Training, 42(3), 333- 342.

Chamberlain, J.M., Terndrup, T.E., Alexander, D.T., Silverstone, F.A., & Wolf-

Klein, G. (1995). Determination of normal ear temperature with an infrared

emission detection thermometer. Annals of Emergency Medicine, 25(1), 15-20.

126 References

Chan, L.S., Cheung, G.T., Lauder, I.J., & Kumana, C.R. (2004). Screening for fever

by remote‐sensing infrared thermographic camera. Journal of Travel Medicine,

11(5), 273-279.

Charkoudian, N. (2003). Skin blood flow in adult human thermoregulation: How it

works, when it does not, and why. Mayo Clinic Proceedings, 78(5), 603-612.

Charkoudian, N., Stephens, D.P., Pirkle, K.C., Kosiba, W.A., & Johnson, J.M.

(1999). Influence of female reproductive hormones on local thermal control of

skin blood flow. Journal of Applied Physiology, 87(5), 1719-1723.

Cheng, C., Matsukawa, T., Sessler, D.I., Makoto, O., Kurz, A., Merrifield, B., . . .

Olofsson, P. (1995). Increasing mean skin temperature linearly reduces the core‐

temperature thresholds for vasoconstriction and shivering in humans.

Anesthesiology, 82(5), 1160-1168.

Chiang, M., Lin, P., Lin, L., Chiou, H., Chien, C., Chu, S., & Chiu, W. (2008). Mass

screening of suspected febrile patients with remote-sensing infrared

thermography: Alarm temperature and optimal distance. Journal of the Formosan

Medical Association, 107(12), 937-944.

Chiu, W., Lin, P., Chiou, H., Lee, W., Lee, C., Yang, Y., . . . Ho, Y. (2005). Infrared

thermography to mass-screen suspected sars patients with fever. Asia-Pacific

Journal of Public Health, 17(1), 26-28.

Cipriano, L.F., & Goldman, R.F. (1975). Thermal responses of unclothed men

exposed to both cold temperatures and high altitudes. Journal of Applied

Physiology, 39(5), 796-800.

Cohen, M.L. (1977). Measurement of the thermal properties of human skin. A

review. Journal of Investigative Dermatology 69(3), 333-338.

Colin, J., Timbal, J., Houdas, Y., Boutelier, C., & Guieu, J. (1971). Computation of

mean body temperature from rectal and skin temperatures. Journal of Applied

Physiology, 31(3), 484-489.

Cooper, T., & Trezek, G. (1971). Correlation of thermal properties of some human

tissue with water content. Aerospace Medicine, 42(1), 24-27.

References 127

Corti, R., Binggeli, C., Sudano, I., Spieker, L., Hänseler, E., Ruschitzka, F., . . . Noll,

G. (2002). Coffee acutely increases sympathetic nerve activity and blood

pressure independently of caffeine content role of habitual versus nonhabitual

drinking. Circulation, 106(23), 2935-2940.

Cortright, R.N., & Koves, T.R. (2000). Sex differences in substrate metabolism and

energy homeostasis. Canadian Journal of Applied Physiology, 25(4), 288-311.

Costello, J., Algar, L., & Donnelly, A. (2012). Effects of whole-body cryotherapy (-

110c) on proprioception and indices of muscle damage. Scandinavian Journal Of

Medicine & Science In Sports, 22(2), 190-198.

Costello, J., Culligan, K., Selfe, J., & Donnelly, A. (2012). Muscle, skin and core

temperature after− 110 C cold air and 8 C water treatment. PloS one, 7(11),

e48190/1-8.

Costello, J., McInerney, C., Bleakley, C., Selfe, J., & Donnelly, A. (2012). The use

of thermal imaging in assessing skin temperature following cryotherapy: A

review. Journal of Thermal Biology, 37(2), 103-110.

Costello, J., Stewart, I., Selfe, J., Karki, A., & Donnelly, A. (2013). Use of thermal

imaging in sports medicine research: A short report. International Sportmed

Journal, 14(2), 94-98.

Crawshaw, L., Nadel, E., Stolwijk, J., & Stamford, B. (1975). Effect of local cooling

on sweating rate and cold sensation. Pflügers Archiv, 354(1), 19-27.

Cuddy, J.S., Buller, M., Hailes, W.S., & Ruby, B.C. (2013). Skin temperature and

heart rate can be used to estimate physiological strain during exercise in the heat

in a cohort of fit and unfit males. Military Medicine, 178(7), 841-847.

Daanen, H. (2003). Finger cold-induced vasodilation: A review. European Journal of


Dancey, C.P., & Reidy, J. (2007). Statistics without maths for psychology. Harlow:

Pearson Education.

Daniels, J.W., Molé, P.A., Shaffrath, J.D., & Stebbins, C.L. (1998). Effects of

caffeine on blood pressure, heart rate, and forearm blood flow during dynamic

leg exercise. Journal of Applied Physiology, 85(1), 154-159.

128 References

Dauncey, M., Haseler, C., Thomas, D.P., & Parr, G. (1983). Influence of a meal on

skin temperatures estimated from quantitative ir-thermography. Experientia,

39(8), 860-862.

Davidson, J., & Bass, A. (1979). Thermography and patello-femoral pain. Acta

Thermographica, 4, 98-103.

Davis, J.K., & Bishop, P.A. (2013). Impact of clothing on exercise in the heat. Sports

Medicine, 43(8), 695-706.

de Dear, R. J., & Brager, G. S. (2002). Thermal comfort in naturally ventilated

buildings: revisions to ASHRAE Standard 55. Energy and buildings, 34(6), 549-

561.

Diakides, N. (1997). New developments in low cost infrared imaging systems.

European Journal of Thermology, 7(4), 213-215.

Dover, G., Borsa, P.A., & McDonald, D.J. (2004). Cold urticaria following an ice

application: A case study. Clinical Journal of Sport Medicine, 14(6), 362-364.

Edge, G., & Morgan, M. (1993). The genius infrared tympanic thermometer.

Anaesthesia, 48(7), 604-607.

Feldman, F., & Nickoloff, E.L. (1984). Normal thermographic standards for the

cervical spine and upper extremities. Skeletal Radiology, 12(4), 235-249.

Fernandes, A.d.A., Amorim, P.R.d.S., Brito, C.J., de Moura, A.G., Moreira, D.G.,

Costa, C.M.A., . . . Marins, J.C.B. (2014). Measuring skin temperature before,

during and after exercise: A comparison of thermocouples and infrared

thermography. Physiological measurement, 35(2), 189-203.

Fernández-Cuevas, I., Marins, J., Carmona, P., García-Concepción, M., Lastras, J., &

Quintana, M. (2012). Reliability and reproducibility of skin temperature of

overweight subjects by an infrared thermography software designed for human

beings. Thermology International, 22(3), 130-137.

Finch, M., Copeland, S., Leahey, W., & Johnston, G. (1988). Short-term effects of

alcohol on peripheral blood flow, platelet aggregation and noradrenaline output

in normal man. International Journal of Tissue Reactions, 10(4), 257-260.

References 129

Flouris, A.D., & Cheung, S.S. (2009). Influence of thermal balance on cold-induced

vasodilation. Journal of Applied Physiology, 106(4), 1264-1271.

Fogleman, M., Fakhrzadeh, L., & Bernard, T.E. (2005). The relationship between

outdoor thermal conditions and acute injury in an aluminum smelter.

International Journal of Industrial Ergonomics, 35(1), 47-55.

Foto, J.G., Brasseaux, D., & Birke, J.A. (2007). Essential features of a handheld

infrared thermometer used to guide the treatment of neuropathic feet. Journal of

the American Podiatric Medical Association, 97(5), 360-365.

Frank, S.M., Beattie, C., Christopherson, R., Norris, E.J., Rock, P., Parker, S., &

Kimball Jr, A.W. (1992). Epidural versus general anesthesia, ambient operating

room temperature, and patient age as predictors of inadvertent hypothermia.


Frank, S.M., Raja, S.N., Bulcao, C.F., & Goldstein, D.S. (1999). Relative

contribution of core and cutaneous temperatures to thermal comfort and

autonomic responses in humans. Journal of Applied Physiology, 86(5), 1588-

1593.

Frascarolo, P., Schutz, Y., & Jequier, E. (1992). Influence of the menstrual cycle on

the sweating response measured by direct calorimetry in women exposed to

warm environmental conditions. European journal of Applied Physiology and

Occupational Physiology, 64(5), 449-454.

Frim, J., Livingstone, S., Reed, L., Nolan, R., & Limmer, R. (1990). Body

composition and skin temperature variation. Journal of Applied Physiology,

68(2), 540-543.

Fritzsche, R. G., & Coyle, E. F. (2000). Cutaneous blood flow during exercise is

higher in endurance-trained humans. Journal of Applied Physiology, 88(2), 738-

744.

Gagge, A.P., & Gonzalez, R.R. (1996). Mechanisms of heat exchange: Biophysics

and physiology. Handbook of Physiology- Environmental Physiology (pp. 45-84).

New York: Oxford University Press.

Gagge, A.P., & Nishi, Y. (1977). Heat exchange between human skin surface and

thermal environment. Bethesda: American Physiological Society.

130 References

Ganio, M.S., Brown, C.M., Casa, D.J., Becker, S.M., & Yeargin, S.W. (2009).

Validity and reliability of devices that assess body temperature during indoor

exercise in the heat. Journal of Athletic Training, 44(2), 124-135.

Gebhart, B., & Pera, L. (1971). The nature of vertical natural convection flows

resulting from the combined buoyancy effects of thermal and mass diffusion.

International Journal of Heat and Mass Transfer, 14(12), 2025-2050.

Gershon-Cohen, J., Borden, A., & Hermel, M. (1969). Thermography of extremities

after smoking. British Journal of Radiology, 42(495), 189-191.

Gershon-Cohen, J., & Habennan, J. (1968). Thermography of smoking. Archives of

Environmental Health: An International Journal, 16(5), 637-641.

Gilligan, D.M., Badar, D.M., Panza, J.A., Quyyumi, A.A., & Cannon, R. (1994).

Acute vascular effects of estrogen in postmenopausal women. Circulation, 90(2),

786-791.

Glickman-Weiss, E., Nelson, A., Hearon, C., Goss, F., Robertson, R., & Cassinelli,

D. (1993). Effects of body morphology and mass on thermal responses to cold

water: Revisited. European Journal of Applied Physiology and Occupational

Physiology, 66(4), 299-303.

Gold, J.E., Cherniack, M., & Buchholz, B. (2004). Infrared thermography for

examination of skin temperature in the dorsal hand of office workers. European

Journal of Applied Physiology, 93(1-2), 245-251.

Gonzalez, R.R., & Sawka, M. (1988). Biophysics of heat transfer and clothing

considerations. Human Performance Physiology and Environmental Medicine at

Terrestrial Extremes (pp. 45-95). Indianapolis: Benchmark.

Goodman, P., Heaslet, M., Pagliano, J., & Rubin, B. (1985). Stress fracture diagnosis

by computer-assisted thermography. Physician and Sports Medicine, 13(4), 114-

132.

Grgić, G., & Pušnik, I. (2011). Analysis of thermal imagers. International Journal of

Thermophysics, 32(1-2), 237-247.

Gross, M., Schuch, C., Huber, E., Scoggins, J., & Sullivan, S. (1988). Method for

quantifying assessment of contact thermography: Effect of extremity dominance

References 131

on temperature distribution patterns. The Journal of Orthopaedic and Sports

Physical Therapy, 10(10), 412-417.

Gun, R., & Budd, G. (1995). Effects of thermal, personal and behavioural factors on

the physiological strain, thermal comfort and productivity of australian shearers

in hot weather. Ergonomics, 38(7), 1368-1384.

Guyton, A., & Hall, J. (2000). Textbook of medical physiology. Philadelphia: WB

Saunder’s Co.

Harada, S., Agarwal, D., & Goedde, H. (1981). Aldehyde dehydrogenase deficiency

as cause of facial flushing reaction to alcohol in japanese. The Lancet, 318(8253),

982.

Hardaker, N., Moss, A., Richards, J., Jarvis, S., McEwan, I., & Selfe, J. (2007).

Relationship between intramuscular temperature and skin surface temperature as

measured by thermal imaging camera. Thermology international, 17(1), 45-50.

Hardy, J.D., Du Bois, E.F., & Soderstrom, G. (1938). The technic of measuring

radiation and convection one figure. The Journal of Nutrition, 15(5), 461-475.

Harper Smith, A.D., Crabtree, D.R., Bilzon, J.L.J., & Walsh, N.P. (2010). The

validity of wireless ibuttons® and thermistors for human skin temperature

measurement. Physiological Measurement, 31(1), 95-114.

Hart, J., & Owens Jr, E.F. (2004). Stability of paraspinal thermal patterns during

acclimation. Journal of Manipulative and Physiological Therapeutics, 27(2),

109-117.

Hasselberg, M.J., McMahon, J., & Parker, K. (2013). The validity, reliability, and

utility of the ibutton for measurement of body temperature circadian rhythms in

sleep/wake research. Sleep Medicine, 14(1), 5-11.

Hausfater, P., Zhao, Y., Defrenne, S., Bonnet, P., & Riou, B. (2008). Cutaneous

infrared thermometry for detecting febrile patients. Emerging Infectious

Diseases, 14(8), 1255-1258.

Herman, C., & Cetingul, M.P. (2011). Quantitative visualization and detection of

skin cancer using dynamic thermal imaging. Journal of Visualized Experiments,

51, 1-3.

132 References

Hershler, C., Conine, T., Nunn, A., & Hannay, M. (1992). Assessment of an infra-red

non-contact sensor for routine skin temperature monitoring: A preliminary study.

Journal of Medical Engineering & Technology, 16(3), 117-122.

Hessemer, V., & Bruck, K. (1985). Influence of menstrual cycle on shivering, skin

blood flow, and sweating responses measured at night. Journal of Applied

Physiology, 59(6), 1902-1910.

Hetsroni, G., Gurevich, M., Mosyak, A., & Rozenblit, R. (2003). Surface

temperature measurement of a heated capillary tube by means of an infrared

technique. Measurement Science and Technology, 14(6), 807-814.

Hildebrandt, C., Raschner, C., & Ammer, K. (2010). An overview of recent

application of medical infrared thermography in sports medicine in austria.

Sensors, 10(5), 4700-4715.

Hirata, K., Nagasaka, T., Hirai, A., Hirashita, M., Takahata, T., & Nunomura, T.

(1986). Effects of human menstrual cycle on thermoregulatory vasodilation

during exercise. European Journal of Applied Physiology and Occupational

Physiology, 54(6), 559-565.

Holowatz, L.A., & Kenney, W.L. (2010). Peripheral mechanisms of

thermoregulatory control of skin blood flow in aged humans. Journal of Applied

Physiology, 109(5), 1538-1544.

Horvath, S., & Drinkwater, B. (1982). Thermoregulation and the menstrual cycle.

Aviation, Space, and Environmental Medicine, 53(8), 790-794.

Horwitz, J.W. (1999). Water at the ice point: A useful quasi-blackbody infrared

calibration source. Applied optics, 38(19), 4053-4057.

Houdas, Y., & Ring, E. (1982). Human body temperature-its measurement and

regulation. New York: Plenum Press.

Huang, C., Wu, Y., Hwang, C., Jong, Y., Chao, C., Chen, W., . . . Yang, W. (2011).

The application of infrared thermography in evaluation of patients at high risk for

lower extremity peripheral arterial disease. Journal of Vascular Surgery, 54(4),

1074-1080.

References 133

Hughes, J.H., Henry, R.E., & Daly, M.J. (1984). Influence of ethanol and ambient

temperature on skin blood flow. Annals of Emergency Medicine, 13(8), 597-600.

Hunt, A., Parker, A., & Stewart, I. (2012). Symptoms of heat illness in surface mine

workers. International Archives of Occupational and Environmental Health,

86(5), 519-527.

Hunt, A., & Stewart, I. (2008). Calibration of an ingestible temperature sensor.

Physiological Measurement, 29(11), 71-78.

International Organisation for Standardisation. (2004a). ISO 7933: Ergonomics of

the thermal environment - analytical determination and interpretation of heat

stress using calculation of the predicted heat strain. Geneva: International

Organization for Standardization.

International Organisation for Standardisation. (2004b). ISO 9886: Ergonomics -

evaluation of thermal strain by physiological measurements. Geneva:

International Organization for Standardization

International Organisation for Standardisation. (2005). ISO 13732/3: Ergonomics of

the thermal environment - assessment of human responses to contact with

surfaces. Part 3 - cold surfaces. Geneva: International Organization for

Standardization.

International Organisation for Standardisation. (2007). ISO 11079: Ergonomics of

the thermal environment - determination and interpretation of cold stress when

using required clothing insulation (ireq) and local cooling effect. Geneva:

International Organization for Standardization.

International Organisation for Standardisation. (2009). ISO 9920: Ergonomics of the

thermal environment - estimation of the thermal insulation and evaporative

resistance of a clothing ensemble. Geneva: International Organization for

Standardization.

Jackson, L.L., & Rosenberg, H.R. (2010). Preventing heat-related illness among

agricultural workers. Journal of Agromedicine, 15(3), 200-215.

Jay, O., Reardon, F.D., Webb, P., Ducharme, M.B., Ramsay, T., Nettlefold, L., &

Kenny, G.P. (2007). Estimating changes in mean body temperature for humans

134 References

during exercise using core and skin temperatures is inaccurate even with a

correction factor. Journal of Applied Physiology, 103(2), 443-451.

Jéquier, E., Gygax, P., Pittet, P., & Vannotti, A. (1974). Increased thermal body

insulation: Relationship to the development of obesity. Journal of Applied

Physiology, 36(6), 674-678.

Joly, H.R., & Weil, M.H. (1969). Temperature of the great toe as an indication of the

severity of shock. Circulation, 39(1), 131-138.

Jones, B.F. (1998). A reappraisal of the use of infrared thermal image analysis in

medicine. IEEE Transactions on Medical Imaging, 17(6), 1019-1027.

Jutte, L.S., Knight, K.L., & Long, B.C. (2008). Reliability and validity of

electrothermometers and associated thermocouples. Journal of Sport

Rehabilitation, 17(1), 50-59.

Jutte, L.S., Knight, K.L., Long, B.C., Hawkins, J.R., Schulthies, S.S., & Dalley, E.B.

(2005). The uncertainty (validity and reliability) of three electrothermometers in

therapeutic modality research. Journal of Athletic Training, 40(3), 207-210.

Jutte, L.S., Long, B.C., & Knight, K.L. (2010). Temperature measurement reliability

and validity with thermocouple extension leads or changing lead temperature.

Journal of Athletic Training, 45(6), 642-624.

Kaciuba-Uscilko, H., & Grucza, R. (2001). Gender differences in thermoregulation.

Current Opinion in Clinical Nutrition & Metabolic Care, 4(6), 533-536.

Kasai, T., Hirose, M., Matsukawa, T., Takamata, A., & Tanaka, Y. (2003). The

vasoconstriction threshold is increased in obese patients during general

anaesthesia. Acta Anaesthesiologica Scandinavica, 47(5), 588-592.

Kelechi, T.J., Good, A., & Mueller, M. (2011). Agreement and repeatability of an

infrared thermometer. Journal of Nursing Measurement, 19(1), 55-64.

Kelechi, T.J., Michel, Y., & Wiseman, J. (2006). Are infrared and thermistor

thermometers interchangeable for measuring localized skin temperature? Journal

of Nursing Measurement, 14(1), 19-30.

Keller, K.H., & Seiler, L. (1971). An analysis of peripheral heat transfer in man.

Journal of Applied Physiology, 30(5), 779-786.

References 135

Kenefick, R.W., Cheuvront, S.N., Palombo, L.J., Ely, B.R., & Sawka, M.N. (2010).

Skin temperature modifies the impact of hypohydration on aerobic performance.

Journal of Applied Physiology, 109(1), 79-86. doi:

10.1152/japplphysiol.00135.2010

Kennet, J., Hardaker, N., Hobbs, S., & Selfe, J. (2007). Cooling efficiency of 4

common cryotherapeutic agents. Journal of Athletic Training, 42(3), 343-348.

Kenney, M., Claassen, D., Bishop, M., & Fels, R. (1998). Regulation of the

sympathetic nerve discharge bursting pattern during heat stress. American

Journal of Physiology-Regulatory, Integrative and Comparative Physiology,

275(6), R1992-R2001.

Kenney, W., & Armstrong, C. (1996). Reflex peripheral vasoconstriction is

diminished in older men. Journal of Applied Physiology, 80(2), 512-515.

Kenney, W., DeGroot, D., & Alexander Holowatz, L. (2004). Extremes of human

heat tolerance: Life at the precipice of thermoregulatory failure. Journal of

Thermal Biology, 29(7), 479-485.

Kerr, Z.Y., Casa, D.J., Marshall, S.W., & Comstock, R.D. (2013). Epidemiology of

exertional heat illness among us high school athletes. American Journal of

Preventive Medicine, 44(1), 8-14.

Klopfenstein, L. (1994). Software linearization techniques for thermocouples,

thermistors, and rtds. Isa Transactions, 33(3), 293-305.

Koban, M., Leis, S., Schultze-Mosgau, S., & Birklein, F. (2003). Tissue hypoxia in

complex regional pain syndrome. Pain, 104(1), 149-157.

Koot, P., & Deurenberg, P. (1995). Comparison of changes in energy expenditure

and body temperatures after caffeine consumption. Annals of Nutrition and

Metabolism, 39(3), 135-142.

Korichi, R., Mac‐Mary, S., Elkhyat, A., Sainthillier, J.M., Ränsch, P., Humbert, P., . .

. Mahé, C. (2006). Development of a new sensor based on micro‐electro‐

mechanical systems for objective in vivo measurement of the cutaneous

temperature: Application to foundations. Skin Research and Technology, 12(3),

206-210.

136 References

Korukçu, M.Ö., & Kilic, M. (2009). The usage of ir thermography for the

temperature measurements inside an automobile cabin. International

Communications in Heat and Mass Transfer, 36(8), 872-877.

Kraning, K., & Gonzalez, R.R. (1991). Physiological consequences of intermittent

exercise during compensable and uncompensable heat stress. Journal of Applied

Physiology, 71(6), 2138-2145.

Krauchi, K., & Wirz-Justice, A. (1994). Circadian rhythm of heat production, heart

rate, and skin and core temperature under unmasking conditions in men.

American Journal of Physiology-Regulatory, Integrative and Comparative

Physiology, 267(3), R819-R829.

Kulka, H.J., & Kenney, W.L. (2002). Heat balance limits in football uniforms: How

different uniform ensembles alter the equation. Physician and Sportsmedicine,

30(7), 29-39.

Kurz, A., Sessler, D.I., Narzt, E., Lenhardt, R., & Lackner, F. (1995). Morphometric

influences on intraoperative core temperature changes. Anesthesia & Analgesia,

80(3), 562-567.

Lahiri, B., Bagavathiappan, S., Jayakumar, T., & Philip, J. (2012). Medical

applications of infrared thermography: A review. Infrared Physics & Technology,

55(4), 221-235.

Lavery, L.A., Higgins, K.R., Lanctot, D.R., Constantinides, G.P., Zamorano, R.G.,

Athanasiou, K.A., . . . Agrawal, C.M. (2007). Preventing diabetic foot ulcer

recurrence in high-risk patients use of temperature monitoring as a self-

assessment tool. Diabetes Care, 30(1), 14-20.

LeBlanc, J. (1954). Subcutaneous fat and skin temperature. Canadian Journal of

Biochemistry and Physiology, 32(4), 354-358.

Lee, J., Shirreffs, S.M., & Maughan, R.J. (2008). Cold drink ingestion improves

exercise endurance capacity in the heat. Medicine & Science in Sports &

Exercise, 40(9), 1637-1644.

Levels, K., de Koning, J.J., Foster, C., & Daanen, H.A.M. (2012). The effect of skin

temperature on performance during a 7.5-km cycling time trial. European

Journal Of Applied Physiology, 112(9), 3387-3395.

References 137

Lewis, H., Foster, A., Mullan, B., Cox, R., & Clark, R. (1969). Aerodynamics of the

human microenvironment. The Lancet, 293(7609), 1273-1277.

Lewis, T. (1930). Observations upon the reactions of the vessels of the human skin to

cold. Heart, 15(2), 177-208.

Lim, C.L., Byrne, C., & Lee, J.K. (2008). Human thermoregulation and measurement

of body temperature in exercise and clinical settings. Annals Academy of

Medicine Singapore, 37(4), 347-353.

Lind, A. (1963). A physiological criterion for setting thermal environmental limits

for everyday work. Journal of Applied Physiology, 18(1), 51-56.

Lipkin, M., & Hardy, J.D. (1954). Measurement of some thermal properties of

human tissues. Journal of applied physiology, 7(2), 212-217.

Livingstone, S., Nolan, R., Frim, J., Reed, L., & Limmer, R. (1987). A

thermographic study of the effect of body composition and ambient temperature

on the accuracy of mean skin temperature calculations. European Journal of

Applied Physiology and Occupational Physiology, 56(1), 120-125.

Liu, C., Chang, R., & Chang, W. (2004). Limitations of forehead infrared body

temperature detection for fever screening for severe acute respiratory syndrome.

Infection Control and Hospital Epidemiology, 25(12), 1109-1111.

Long, B.C., Jutte, L.S., & Knight, K.L. (2010). Response of thermocouples

interfaced to electrothermometers when immersed in 5 water bath temperatures.

Journal of Athletic Training, 45(4), 338-343.

Ludwig, N., Formenti, D., Gargano, M., & Alberti, G. (2014). Skin temperature

evaluation by infrared thermography: Comparison of image analysis methods.

Infrared Physics & Technology, 62(2014), 1-6.

Lundgren, K., Kuklane, K., Gao, C., & Holmer, I. (2013). Effects of heat stress on

working populations when facing climate change. Industrial Health, 51(1), 3-15.

Lyklema, J. (2001). Surface conduction. Journal of Physics: Condensed Matter,

13(21), 5027-5034.

Machin, G., Simpson, R., & Broussely, M. (2009). Calibration and validation of

thermal imagers. Quantitative InfraRed Thermography Journal, 6(2), 133-147.

138 References

Mairiaux, P., & Malchaire, J. (1985). Workers self-pacing in hot conditions: A case

study. Applied Ergonomics, 16(2), 85-90.

Mannara, G., Salvatori, G., & Pizzuti, G. (1993). Ethyl alcohol induced skin

temperature changes evaluated by thermography. Preliminary results. Bollettino

Della Societa Italiana di Biologia Sperimentale, 69(10), 587-594.

Maron, B.J., Doerer, J.J., Haas, T.S., Tierney, D.M., & Mueller, F.O. (2009). Sudden

deaths in young competitive athletes analysis of 1866 deaths in the united states,

1980–2006. Circulation, 119(8), 1085-1092.

Mathews, S.C., Narotsky, D.L., Bernholt, D.L., Vogt, M., Hsieh, Y.H., Pronovost,

P.J., & Pham, J.C. (2012). Mortality among marathon runners in the united states,

2000-2009. The American Journal of Sports Medicine, 40(7), 1495-1500.

Matsukawa, T., Ozaki, M., Nishiyama, T., Imamura, M., & Kumazawa, T. (2000).

Comparison of infrared thermometer with thermocouple for monitoring skin

temperature. Critical Care Medicine, 28(2), 532-536.

Mayr, H. (1995). Thermographic evaluation after knee surgery. The Thermal Image

in Medicine and Biology (pp.182-187). Vienna: Uhlen-Verlag.

McArdle, W.D., Toner, M.M., Magel, J.R., Spinal, R.J., & Pandolf, K.B. (1992).

Thermal responses of men and women during cold-water immersion: Influence

of exercise intensity. European Journal of Applied Physiology and Occupational

Physiology, 65(3), 265-270.

Meknas, K., Odden-Miland, Å., Mercer, J.B., Castillejo, M., & Johansen, O. (2008).

Radiofrequency microtenotomy a promising method for treatment of recalcitrant

lateral epicondylitis. The American Journal of Sports Medicine, 36(10), 1960-

1965.

Merla, A., Mattei, P.A., Di Donato, L., & Romani, G.L. (2010). Thermal imaging of

cutaneous temperature modifications in runners during graded exercise. Annals of

Biomedical Engineering, 38(1), 158-163.

Meyer, A.A., Kundt, G., Steiner, M., Schuff-Werner, P., & Kienast, W. (2006).

Impaired flow-mediated vasodilation, carotid artery intima-media thickening, and

elevated endothelial plasma markers in obese children: The impact of

cardiovascular risk factors. Pediatrics, 117(5), 1560-1567.

References 139

Mitchell, D., & Wyndham, C. (1969). Comparison of weighting formulas for

calculating mean skin temperature. Journal of Applied Physiology, 26(5), 616-

622.

Modest, M.F. (2013). Radiative heat transfer. New York: McGraw-Hill.

Moeller, J.L., Monroe, J., & McKeag, D.B. (1997). Cryotherapy-induced common

peroneal nerve palsy. Clinical Journal of Sport Medicine, 7(3), 212-216.

Mora-Rodriguez, R., Del Coso, J., Aguado-Jimenez, R., & Estevez, E. (2007).

Separate and combined effects of airflow and rehydration during exercise in the

heat. Medicine & Science in Sports & Exercise, 39(10), 1720-1726.

Moran, D. (2002). Core temperature measurement. Sports Medicine, 32(14), 879-

885.

Mueller, F.O., & Cantu, R.C. (2010). Catastrophic sports injury research: Twenty

eighth annual report: Fall 1982 - spring 2010. from

www.unc.edu/depts/nccsi/2010allsport.pdf

Mueller, F.O., & Colgate, B. (2013). Annual survey of football injury research:

1931–2012. from http://www.unc.edu/depts/nccsi/2012FBInj.pdf

Nadel, E., Bullard, R., & Stolwijk, J. (1971). Importance of skin temperature in the

regulation of sweating. Journal of Applied Physiology, 31(1), 80-87.

Nadel, E., Mitchell, J., & Stolwijk, J. (1973). Differential thermal sensitivity in the

human skin. Pflügers Archiv, 340(1), 71-76.

Nadel, E., Wenger, C., Roberts, M., Stolwijk, J., & Cafarelli, E. (1977).

Physiological defenses against hyperthermia of exercise. Annals of the New York

Academy of Sciences, 301(1), 98-109.

Nag, P.K., & Nag, A. (2001). Shiftwork in the hot environment. Journal of Human

Ergology, 30(1-2), 161-166.

Nakayama, T., Suzuki, M., & Ishizuka, N. (1975). Action of progesterone on

preoptic thermosensitive neurones. Nature, 258(5530), 80.

Namdar, M., Schepis, T., Koepfli, P., Gaemperli, O., Siegrist, P.T., Grathwohl, R., . .

. Wyss, C.A. (2009). Caffeine impairs myocardial blood flow response to

140 References

physical exercise in patients with coronary artery disease as well as in age-

matched controls. PloS One, 4(5), e5665/1-6.

Nelson, N.G., Collins, C.L., Comstock, R.D., & McKenzie, L.B. (2011). Exertional

heat-related injuries treated in emergency departments in the us, 1997–2006.

American Journal of Preventive Medicine, 40(1), 54-60.

Ng, D., Chan, C., Chan, E., Kwok, K., Chow, P., Lau, W., & Ho, J. (2005). A brief

report on the normal range of forehead temperature as determined by noncontact,

handheld, infrared thermometer. American Journal of Infection Control, 33(4),

227-229.

Ng, E. (2009). A review of thermography as promising non-invasive detection

modality for breast tumor. International Journal of Thermal Sciences, 48(5), 849-

859.

Nguyen, A., Cohen, N.J., Lipman, H., Brown, C.M., Molinari, N., Jackson, W.L., . . .

Salhi, B.A. (2010). Comparison of 3 infrared thermal detection systems and self-

report for mass fever screening. Emerging Infectious Diseases, 16(11), 1710.

Nielsen, B., Savard, G., Richter, E., Hargreaves, M., & Saltin, B. (1990). Muscle

blood flow and muscle metabolism during exercise and heat stress. Journal of


Nielsen, M. (1938). Die regulation der körpertemperatur bei muskelarbeit (the

regulation of body temperature during muscular work). Skandinavisches Archiv

für Physiologie, 79(2), 193-230.

Niu, H.H., Lui, P.W., Hu, J.S., Ting, C.K., Yin, Y.C., Lo, Y.L., . . . Lee, T.Y. (2001).

Thermal symmetry of skin temperature: Normative data of normal subjects in

taiwan. Chinese Medical Journal, 64(8), 459-468.

Ochs, M., Horbach, T., Schulz, A., Koch, R., & Bauer, H. (2009). A novel

calibration method for an infrared thermography system applied to heat transfer

experiments. Measurement Science and Technology, 20(7), 1-9.

Ohhashi, T., Sakaguchi, M., & Tsuda, T. (1998). Human perspiration measurement.

Physiological Measurement, 19(4), 449.

References 141

Olesen, B.W. (1984). How many sites are necessary to estimate a mean skin

temperature? New York: Raven Press.

Park, Y., Iwamoto, J., Tajima, F., Miki, K., Park, Y., & Shiraki, K. (1988). Effect of

pressure on thermal insulation in humans wearing wet suits. Journal of Applied

Physiology, 64(5), 1916-1922.

Pascoe, D.D., Barberio, M., Elmer, D., & Wolfe, R.L. (2012). Potential errors in

mean skin temperature calculation due to thermistor placement as determined by

infrared thermography. Thermology International, 22(3), 42-48.

Peter, T. (2003). Heat balance precedes stabilization of body temperatures during

cold water immersion. Journal of Applied Physiology, 95(1), 89-96.

Petrofsky, J.S., Lohman, E., Suh, H.J., Garcia, J., Anders, A., Sutterfield, C., &

Khandge, C. (2006). The effect of aging on conductive heat exchange in the skin

at two environmental temperatures. Medical Science Monitor, 12(10), 400-408.

Pivarnik, J.M., Marichal, C.J., Spillman, T., & Morrow, J. (1992). Menstrual cycle

phase affects temperature regulation during endurance exercise. Journal of


Plassmann, P., Ring, E., & Jones, C. (2006). Quality assurance of thermal imaging

systems in medicine. Thermology international, 16(1), 10-15.

Prek, M., & Butala, V. (2010). Principles of energy analysis of human heat and mass

exchange with the indoor environment. International Journal of Heat and Mass

Transfer, 53(25), 5806-5814.

Prentice, A.M., Black, A., Coward, W., Davies, H., Goldberg, G., Murgatroyd, P., . .

. Whitehead, R. (1986). High levels of energy expenditure in obese women.

British Medical Journal (Clinical research ed.), 292(6526), 983-987.

Price, M.J. (2006). Thermoregulation during exercise in individuals with spinal cord

injuries. Sports Medicine, 36(10), 863-879.

Psikuta, A., Niedermann, R., & Rossi, R.M. (2013). Effect of ambient temperature

and attachment method on surface temperature measurements. International

Journal Of Biometeorology, In Press.

142 References

Qi, H., & Diakides, N.A. (2007). Infrared imaging in medicine. Boca Raton: CRC

Press.

Quinlan, P., Lane, J., & Aspinall, L. (1997). Effects of hot tea, coffee and water

ingestion on physiological responses and mood: The role of caffeine, water and

beverage type. Psychopharmacology, 134(2), 164-173.

Quinlan, P., Lane, J., Moore, K.L., Aspen, J., Rycroft, J.A., & O'Brien, D.C. (2000).

The acute physiological and mood effects of tea and coffee: The role of caffeine

level. Pharmacology Biochemistry and Behavior, 66(1), 19-28.

Ramanathan, N. (1964). A new weighting system for mean surface temperature of

the human body. Journal of Applied Physiology, 19(3), 531-533.

Randall, W.C. (1946). Quantitation and regional distribution of sweat glands in man.

Journal of Clinical Investigation, 25(5), 761-767.

Raymann, R.J., Swaab, D.F., & Van Someren, E.J. (2007). Skin temperature and

sleep-onset latency: Changes with age and insomnia. Physiology & Behavior,

90(2), 257-266.

Rees, W., & James, S. (1992). Angular variation of the infrared emissivity of ice and

water surfaces. International Journal of Remote Sensing, 13(15), 2873-2886.

Ring, E. (2007). The historical development of temperature measurement in

medicine. Infrared Physics & Technology, 49(3), 297-301.

Ring, E., & Ammer, K. (2000). The technique of infrared imaging in medicine.

Thermology International, 10(1), 7-14.

Ring, E., & Ammer, K. (2012). Infared thermal imaging in medicine. Physiological

Measurement, 33(3), 33-46.

Ring, E., Ammer, K., Wiecek, B., Plassmann, P., Jones, C., Jung, A., & Murawski,

P. (2007). Quality assurance for thermal imaging systems in medicine.

Thermology International, 17(3), 103-106.

Ring, E., Engel, J., & Page-Thomas, D. (1984). Thermologic methods in clinical

pharmacology-skin temperature measurement in drug trials. International

Journal of Clinical Pharmacology, Therapy, and Toxicology, 22(1), 20-24.

References 143

Ring, E., Jung, A., Zuber, J., Rutowski, P., Kalicki, B., & Bajwa, U. (2008).

Detecting fever in polish children by infrared thermography. Paper presented at

the QIRT, Krakow, Poland.

Risbo, A., Hagelsten, J., & Jessen, K. (1981). Human body temperature and

controlled cold exposure during moderate and severe experimental alcohol‐

intoxication. Acta Anaesthesiologica Scandinavica, 25(3), 215-218.

Rosenthal, N.E., Levendosky, A.A., Skwerer, R.G., Joseph-Vanderpool, J.R., Kelly,

K.A., Hardin, T., . . . Wehr, T.A. (1990). Effects of light treatment on core body

temperature in seasonal affective disorder. Biological Psychiatry, 27(1), 39-50.

Ross, M., Abbiss, C., Laursen, P., Martin, D., & Burke, L. (2013). Precooling

methods and their effects on athletic performance. Sports Medicine, 43(3), 207-

225.

Rothchild, I., & Barnes, A. (1952). The effects of dosage, and of estrogen, androgen

or salicylate administration on the degree of body temperature elevation induced

by progesterone. Endocrinology, 50(4), 485-496.

Rothwell, N.J., & Stock, M.J. (1983). Diet-induced thermogenesis. In G. L & S. M. J

(Eds.), Mammalian thermogenesis (pp. 208-233). Netherlands: Springer

Rowell, L.B. (2011). Cardiovascular adjustments to thermal stress Comprehensive

physiology (pp. 967-1023). United States Of America: John Wiley & Sons.

Roy, R.A., Boucher, J.P., & Comtois, A.S. (2006a). Digitized infrared segmental

thermometry: Time requirements for stable recordings. Journal of Manipulative

& Physiological Therapeutics, 29(6), 468.e461-468.e410.

Roy, R.A., Boucher, J.P., & Comtois, A.S. (2006b). Validity of infrared thermal

measurements of segmental paraspinal skin surface temperature. Journal of

Manipulative & Physiological Therapeutics, 29(2), 150-155.

Ruopsa, N., Kujala, S., Kaarela, O., Ohtonen, P., & Ryhänen, J. (2009). Wireless

infrared thermometer in the follow-up of finger temperatures. The Journal of

Hand Surgery, 34(4), 526-529.

144 References

Rutkove, S.B., Veves, A., Mitsa, T., Nie, R., Fogerson, P.M., Garmirian, L.P., &

Nardin, R.A. (2009). Impaired distal thermoregulation in diabetes and diabetic

polyneuropathy. Diabetes Care, 32(4), 671-676.

Safe Work Australia. (2012). The cost of work-related injury and illness for

australian employers, workers and the community: 2008–09. Retrieved from

http://www.safeworkaustralia.gov.au/sites/swa/about/publications/pages/cost-

injury-illness-2008-09.

Sanchez-Marin, F., Calixto-Carrera, S., & Villaseñor-Mora, C. (2009). Novel

approach to assess the emissivity of the human skin. Journal of Biomedical

Optics, 14(2), 024006-024012.

Sarabia, J., Rol, M., Mendiola, P., & Madrid, J. (2008). Circadian rhythm of wrist

temperature in normal-living subjects: A candidate of new index of the circadian

system. Physiology & Behavior, 95(4), 570-580.

Savastano, D.M., Gorbach, A.M., Eden, H.S., Brady, S.M., Reynolds, J.C., &

Yanovski, J.A. (2009). Adiposity and human regional body temperature. The

American Journal of Clinical Nutrition, 90(5), 1124-1131.

Sawka, M., Cheuvront, S., & Kenefick, R. (2012). High skin temperature and

hypohydration impair aerobic performance. Experimental Physiology, 97(3),

327-332.

Sawka, M., & Coyle, E. (1999). Influence of body water and blood volume on

thermoregulation and exercise performance in the heat. Exercise and Sport

Sciences Reviews, 27(1), 167-218.

Sawka, M., Latzka, W., Matott, R., & Montain, S. (1998). Hydration effects on

temperature regulation. International Journal of Sports Medicine, 19(S2), S108-

S110.

Sawka, M., & Wenger, C.B. (1988). Physiological responses to acute exercise-heat

stress. Natick: Army Research Institute of Environmental Medicine.

Sawka, M.N., Leon, L.R., Montain, S.J., & Sonna, L.A. (2011). Integrated

physiological mechanisms of exercise performance, adaptation, and

maladaptation to heat stress. Comprehensive Physiology, 1, 1883-1928.

References 145

Schlader, Z.J., Simmons, S.E., Stannard, S.R., & Mundel, T. (2011). Skin

temperature as a thermal controller of exercise intensity. European Journal of


Selfe, J., Hardaker, N., Thewlis, D., & Karki, A. (2006). An accurate and reliable

method of thermal data analysis in thermal imaging of the anterior knee for use in

cryotherapy research. Archives of Physical Medicine & Rehabilitation, 87(12),

1630-1635.

Selfe, J., Hardaker, N., Whitaker, J., & Hayes, C. (2007). Thermal imaging of an ice

burn over the patella following clinically relevant cryotherapy application during

a clinical research study. Physical Therapy in Sport, 8(3), 153-158.

Selfe, J., Whitaker, J., & Hardaker, N. (2008). A narrative literature review

identifying the minimum clinically important difference for skin temperature

asymmetry at the knee. Thermology International, 18(2), 51-54.

Sessler, D.I., McGuire, J., & Sessler, A.M. (1991). Perioperative thermal insulation.


Shuran, M., & Nelson, R.A. (1991). Quantitation of energy expenditure by infrared

thermography. The American Journal of Clinical Nutrition, 53(6), 1361-1367.

Siegel, R., Mate, J., Brearley, M.B., Watson, G., Nosaka, K., & Laursen, P.B. (2010).

Ice slurry ingestion increases core temperature capacity and running time in the

heat. Medicine & Science in Sports & Exercise, 42(4), 717-725.

Siegel, R., Maté, J., Watson, G., Nosaka, K., & Laursen, P.B. (2012). Pre-cooling

with ice slurry ingestion leads to similar run times to exhaustion in the heat as

cold water immersion. Journal of Sports Sciences, 30(2), 155-165.

Simon, E., Pierau, F.-K., & Taylor, D. (1986). Central and peripheral thermal control

of effectors in homeothermic temperature regulation. Physiological Reviews,

66(2), 235-300.

Simpson, R., Machin, G., McEvoy, H., & Rusby, R. (2006). Traceability and

calibration in temperature measurement: A clinical necessity. Journal of Medical

Engineering & Technology, 30(4), 212-217.

146 References

Smith, C.J., & Havenith, G. (2012). Body mapping of sweating patterns in athletes:

A sex comparison. Medicine & Science in Sports & Exercise, 44(12), 2350-2361.

Sørensen, L.T., Jørgensen, S., Petersen, L.J., Hemmingsen, U., Bülow, J., Loft, S., &

Gottrup, F. (2009). Acute effects of nicotine and smoking on blood flow, tissue

oxygen, and aerobe metabolism of the skin and subcutis. Journal of Surgical

Research, 152(2), 224-230.

Spalding, S.J., Kwoh, C.K., Boudreau, R., Enama, J., Lunich, J., Huber, D., . . .

Hirsch, R. (2008). Three-dimensional and thermal surface imaging produces

reliable measures of joint shape and temperature: A potential tool for quantifying

arthritis. Arthritis Research and Therapy, 10(1), 1-9.

Steketee, J. (1973). Spectral emissivity of skin and pericardium. Physics in Medicine

and Biology, 18(5), 686-694.

Steketee, J. (1976). The influence of cosmetics and ointments on the spectral

emissivity of skin (skin temperature measurement). Physics in Medicine and

Biology, 21(6), 920-930.

Stoll, A.M., & Hardy, J.D. (1950). Study of thermocouples as skin thermometers.

Journal of Applied Physiology, 2(10), 531-543.

Stolwijk, J., & Hardy, J. (1966). Partitional calorimetric studies of responses of man

to thermal transients. Journal of Applied Physiology, 21(3), 967-977.

Sudhir, K., Esler, M.D., Jennings, G.L., & Komesaroff, P.A. (1997). Estrogen

supplementation decreases norepinephrine-induced vasoconstriction and total

body norepinephrine spillover in perimenopausal women. Hypertension, 30(6),

1538-1543.

Sundberg, S. (1984). Acute effects and long-term variations in skin blood flow

measured with laser doppler flowmetry. Scandinavian journal of clinical &

laboratory investigation, 44(4), 341-345.

Tan, J.-H., Ng, E., Rajendra Acharya, U., & Chee, C. (2009). Infrared thermography

on ocular surface temperature: A review. Infrared Physics & Technology, 52(4),

97-108.

References 147

Thomas, R. (2006). Sensors and Handheld Devices for Surface Measurement of Skin

Temperature. Handbook of Non-Invasive Methods and the Skin (pp. 753-768).

Boca Raton: CRC Press.

Togawa, T. (1989). Non-contact skin emissivity: Measurement from reflectance

using step change in ambient radiation temperature. Clinical Physics and


Togawa, T., & Saito, H. (1994). Non-contact imaging of thermal properties of the

skin. Physiological Measurement, 15(3), 291-298.

Tucker, R. (2009). The anticipatory regulation of performance: The physiological

basis for pacing strategies and the development of a perception-based model for

exercise performance. British Journal of Sports Medicine, 43(6), 392-400.

Tucker, R., Marle, T., Lambert, E. V., & Noakes, T. D. (2006). The rate of heat

storage mediates an anticipatory reduction in exercise intensity during cycling at

a fixed rating of perceived exertion. The Journal of physiology, 574(3), 905-

915.Blattis et al 2001

Tyler, C.J. (2011). The effect of skin thermistor fixation method on weighted mean

skin temperature. Physiological Measurement, 32(10), 1541-1547.

Uematsu, S. (1985a). Symmetry of skin temperature comparing one side of the body

to the other. Thermology, 1(1), 4-7.

Uematsu, S. (1985b). Thermographic imaging of cutaneous sensory segment in

patients with peripheral nerve injury: Skin-temperature stability between sides of

the body. Journal of Neurosurgery, 62(5), 716-720.

Usuki, K., Kanekura, T., Aradono, K., & Kanzaki, T. (1998). Effects of nicotine on

peripheral cutaneous blood flow and skin temperature. Journal of

Dermatological Science, 16(3), 173-181.

van den Heuvel, C.J., Ferguson, S.A., Dawson, D., & Gilbert, S.S. (2003).

Comparison of digital infrared thermal imaging (diti) with contact thermometry:

Pilot data from a sleep research laboratory. Physiological Measurement, 24(3),

717-725

148 References

van Marken Lichtenbelt, W.D., Daanen, H.A.M., Wouters, L., Fronczek, R.,

Raymann, R.J.E.M., Severensf, N.M.W., & Van Someren, E.J.W. (2006).

Evaluation of wireless determination of skin temperature using ibuttons.

Physiology & Behavior, 88(4), 489-497.

Van Someren, E.J., Raymann, R.J., Scherder, E.J., Daanen, H.A., & Swaab, D.F.

(2002). Circadian and age-related modulation of thermoreception and

temperature regulation: Mechanisms and functional implications. Ageing

Research Reviews, 1(4), 721-778.

Vardasca, R. (2008). Symmetry of temperature distribution in the upper and lower

extremities. Thermology International, 18(4), 154-155.

Vaughan, M.S., Vaughan, R.W., & Cork, R.C. (1981). Postoperative hypothermia in

adults relationship of age, anesthesia, and shivering to rewarming. Anesthesia &

Analgesia, 60(10), 746-751.

Verbraecken, J., Van de Heyning, P., De Backer, W., & Van Gaal, L. (2006). Body

surface area in normal-weight, overweight, and obese adults. A comparison

study. Metabolism, 55(4), 515-524.

Versey, N.G., Gore, C.J., Halson, S.L., Plowman, J.S., & Dawson, B.T. (2011).

Validity and reliability of temperature measurement by heat flow thermistors,

flexible thermocouple probes and thermistors in a stirred water bath.


Vitiello, M.V., Smallwood, R.G., Avery, D.H., Pascualy, R.A., Martin, D.C., &

Prinz, P.N. (1986). Circadian temperature rhythms in young adult and aged men.

Neurobiology of Aging, 7(2), 97-100.

Wang, D., Zhang, H., Arens, E., & Huizenga, C. (2007). Observations of upper-

extremity skin temperature and corresponding overall-body thermal sensations

and comfort. Building and Environment, 42(12), 3933-3943.

Wasner, G., Schattschneider, J., & Baron, R. (2002). Skin temperature side

differences – a diagnostic tool for crps? Pain, 98(1), 19-26.

Watmough, D., Fowler, P.W., & Oliver, R. (1970). The thermal scanning of a curved

isothermal surface: Implications for clinical thermography. Physics in Medicine

and Biology, 15(1), 1-8.

References 149

Weatherby, J. (1942). Skin temperature changes caused by smoking and other

sympathomimetic stimuli. American Heart Journal, 24(1), 17-30.

Webb, P. (1992). Temperatures of skin, subcutaneous tissue, muscle and core in

resting men in cold, comfortable and hot conditions. European Journal of

Applied Physiology and Occupational Physiology, 64(5), 471-476.

Wegmann, M., Faude, O., Poppendieck, W., Hecksteden, A., Fröhlich, M., & Meyer,

T. (2012). Pre-cooling and sports performance. Sports Medicine, 42(7), 545-564.

Wenger, C.B. (1972). Heat of evaporation of sweat: Thermodynamic considerations.

Journal of applied physiology, 32(4), 456-459.

West, R.J., & Russell, M. (1987). Cardiovascular and subjective effects of smoking

before and after 24 h of abstinence from cigarettes. Psychopharmacology, 92(1),

118-121.

Westerterp-Plantenga, M., Wouters, L., & Ten Hoor, F. (1990). Deceleration in

cumulative food intake curves, changes in body temperature and diet-induced

themogenesis. Physiology & Behavior, 48(6), 831-836.

Wilson, O., & Goldman, R.F. (1970). Role of air temperature and wind in the time

necessary for a finger to freeze. Journal of Applied Physiology, 29(5), 658-664.

Winslow, C.-E., Herrington, L., & Gagge, A.P. (1936). A new method of partitional

calorimetry. American Journal of Physiology-Legacy Content, 116(3), 641-655.

Wolf, R., Tüzün, B., & Tüzün, Y. (1999). Alcohol ingestion and the cutaneous

vasculature. Clinics in Dermatology, 17(4), 395-403.

Wood, S., Mangum, B., Filliben, J., & Tillett, S. (1978). An investigation of the

stability of thermistors. Journal of Research of the National Bureau of Standards,

83(3), 247-263.

Yadav, B., Srivastava, R., Singh, S., Kumar, A., & Yadav, A. (2012). Temperature

sensors based on semiconducting oxides: An overview. Condensed Matter,1-22.

Yard, E.E., Gilchrist, J., Haileyesus, T., Murphy, M., Collins, C., McIlvain, N., &

Comstock, R.D. (2010). Heat illness among high school athletes—united states,

2005–2009. Journal of Safety Research, 41(6), 471-474.

150 References

Yosipovitch, G., Xiong, G.L., Haus, E., Sackett-Lundeen, L., Ashkenazi, I., &

Maibach, H.I. (1998). Time-dependent variations of the skin barrier function in

humans: Transepidermal water loss, stratum corneum hydration, skin surface ph,

and skin temperature. Journal of investigative dermatology, 110(1), 20-24.

Zaproudina, N., Airaksinen, O., & Närhi, M. (2013). Are the infrared thermography

findings skin temperature‐dependent? A study on neck pain patients. Skin

Research and Technology, 19(1), 537-544.

Zaproudina, N., Varmavuo, V., Airaksinen, O., & Närhi, M. (2008). Reproducibility

of infrared thermography measurements in healthy individuals. Physiological

Measurement, 29(4), 515-524.

INTERCHANGEABILITY OF INFRARED AND C DEVICES ...Interchangeability of Infrared and Conductive...

Documents

Transcript of INTERCHANGEABILITY OF INFRARED AND C DEVICES ...Interchangeability of Infrared and Conductive...