January, 2014 1 Innovation for Neonatal Care at Philips Research Dr Louis Atallah Senior Scientist,...

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January, 2014 1 Innovation for Neonatal Care at Philips Research Dr Louis Atallah Senior Scientist, Patient Care Solutions Philips Research, Eindhoven January 2014

Transcript of January, 2014 1 Innovation for Neonatal Care at Philips Research Dr Louis Atallah Senior Scientist,...

January, 20141

Innovation for Neonatal Care at Philips Research

Dr Louis AtallahSenior Scientist, Patient Care SolutionsPhilips Research, EindhovenJanuary 2014

January, 20142

Philips Research: Innovation around the GlobeMore than 1500 scientists, cooperating with ~250 universities/institutes

Briarcliff Clinical sites HealthcareLighting

CambridgeHome & OralHealthcare

Paris Healthcare

Eindhoven HealthcareLighting Lifestyle

Bangalore Emerging Markets HealthcareLighting

HamburgHealthcare

Shanghai Emerging Markets HealthcareLighting, Lifestyle

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Patient Care SolutionsEnhancing patient care through smart sensor solutions

VisionSmart patient care solutions will increasingly support hospital staff in clinical decision making in various care settings. New solutions for lower acuity care will reduce the workload in the ICU. This will also enable use in the home, aiming to improve quality of life and further drive down the cost of healthcare.

MissionThrough collaboration with clinical experts we deliver innovative technology solutions for Patient Care in the fields of Physiological Monitoring, Respiratory & Emergency care, assisting caregivers both in hospital and home.

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Why neonatal care?• 15 million babies are born preterm every year (WHO)• Many babies (not only preterm) have problems and require care in

the NICU (Sweden: 10%). • Term babies could also be challenging as their problems require quick

diagnosis and treatment.• Very ill babies need more observation and care and often have longer

stays in NICUs than preterm babies.

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4 million newborns die every year, most from easily preventable causes

Source: Lawn, Joy E., Simon Cousens and Jelka Zupan, ‘4 million neonatal deaths; When? Where? Why?', The Lancet, vol. 365, no. 9462,5 March 2005, p. 895.

Source: World Health Organization

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30 Mncases

In emerging markets, over 25% of neonates born suffer from hyperbilirubinea

Neonatal deaths (0–28 days) per 1,000 live births, 2004

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NICU Requirements

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Child

Monitoring

Family

Procedures Diagnosis/Screening

Life Support

ThermoregulationNutritionAffective SupportCalm Environment

Ventilation/CPAPOxygen therapyBio-isolation

GrowthSupport

Treatment

AccessKangaroo Care

X-RayUltrasoundCranial UltrasoundEEGPhysical ExaminationROP-screening

MedicationPhototherapyBrain CoolingSurfactantInhaled Nitric Oxide

Heart RateBreathing Rate

Oxygen SaturationIBP and NIBP

CFMTemperatureCapnography

Blood GasBody Weight

Intravenous Line PlacementUmbilical Artery/Vein CatherizationBlood SamplingDiaper ChangingRoutine CareEndotracheal IntubationTactile stimulationResuscitation

* Not exhaustive

AdministrationTraining Environment

ThermoregulationHumidityAffective SupportCalm EnvironmentLighting ConditionsIntegration

Multidisciplinary team trainingBaby mannequins

Patient RecordMedication ControlTreatment logging

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This presentationEnhancing neonatal care through smart sensor solutions

Focus on:• Thermoregulation and unobtrusive

temperature measurement• Unobtrusive ECG monitoring• Can monitoring help us predict

complications and prevent them earlier?

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Thermoregulation and core temperature measurement

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Thermoregulation

• Thermoregulation is the ability to balance between heat production and heat loss in order to maintain body temperature within a certain normal range.

• Need for thermoregulation: – To protect enzyme function

– To maximize metabolic efficiency– To reduce oxygen use– To reduce calorie expenditure – To promote growth and development

• New born babies are highly susceptible for heat loss and its adverse consequences (hypothermia) immediately after birth and during first few days of life.

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Modes of Heat Loss

High surface area to volume ratio A lack of thermal insulation Thin non-keratinized skin

(60-80 W/m²)(25 W/m²)

(50 W/m²)

(Negligible)

Heat Loss at Birth

Inadequate storage Poor vasomotor response

Reasons for increased susceptibility to heat Loss in neonates

How best to measure neonatal temperature?

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Several methods for measuring temperatureContinuous, accurate?

• Spot-check temperature measurements (axillary)• Sensors in the diaper (isolated)• Rectal temperatures?• Do they really represent core temperature?

• Esophageal Temperature:– Surrogate for core temperature– Temperature changes can be sudden and

dramatic, not reflected by spot-check measurements.

Philips InnerSense Esophageal Temperature Probe+ Feeding Tube

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Philips InnerSense Esophageal Temperature Probe+ Feeding Tube

Unobtrusive core temperature measurement

• A feeding tube containing temperature sensors to reliably measure core temperature.

• Temperature can be measured, displayed on the patient monitor and used for trend analysis.

• Recent study we did on 12 babies showed that this sensor is more stable than a skin sensor placed in the diaper especially during motion and kangaroo care.

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Contactless ECG

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NICU| Environment

• Many procedures are necessary and standard, and have reduced viability to 24 weeks. However, these same procedures can have side effects!

• Skin is incompletely developed (not until 34 weeks that the skin is functionally competent). Scars prevail in 10% of neonates in the NICU.

• ECG is important in observing neonatal conditions and can indicate life threatening events such as sepsis (infection).

• A closer look….

Adhesive electrodes

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Neonate: improved comfort (less scars and pain)

Caregiver: less preparation time

Parents: improved parent-child bonding

Embedded neonatal monitoring| ENEMO

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The trial| Contactless capacitive ECG• Trial at the Maxima Medical Centre, Veldhoven, NL. Clinical data of 20 neonates (100

hours of data) + Reference- Camera- Notes.• Primary objective: Evaluate the performance of capacitive ECG against adhesive ECG.• Secondary objective: Learn about conditions in the NICU. What are the (un)desired

conditions for an optimal recording?

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Motion levels|babies are different

Total time 3.75 hours Total time: 5.7 hours

37%

7%

56%

18%

13%

69%

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Framework| The Vectorcardiogram

A graphic representation of the magnitude and direction of the electrical currents in the heart as a vector loop.

Vectorcardiogram (VCG)

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VCG construction

Framework| ECG reconstruction

Pre-processing/ subtracting motion artefacts

VCG Projection

ECG R-peak identification using wavelet techniques

Kalman filtering of channels (knowing beat locations)

VCG Projection (again)

Project on standard Einthoven leads

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Reference ECGCapacitive ECG

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Framework| In real time…

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Results| Instantaneous Heart Rate coverage

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Perc

ent c

over

age

Baby number

Coverage: Total time with a good match.

Peak detection used to calculate true positives and negatives leading to Sensitivity and PPV.

Reference ECGCapacitive ECG

Coverage Low number of layers, mostly chest position, good sensor alignment

Very bad sensor alignment, side positioning

Perc

ent c

over

age

Baby number

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Good conditions

Results| Effect of layers and positioningBaby 9

4 layers of cloth, side positioning 1 layer removed, chest positioning

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Bad conditions

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Results| When it’s good it’s really good

Baby 1: Overall Coverage: 86%, max time to wait for a good iHR: 4.1 sec.

No Motion Low Motion Intervention

Per

cen

tag

e

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Results| ECG shape analysisParameter Mean difference (std)

in ms

RR distance -0.35(7.94)

QRS distance -6.1 (6.71)

PR distance 19.78(11.24)

QT distance -33.56(30.65)

Reference

Capacitive

R

P T

QS

R

P

T

Q

S

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For more results see: PR-TN 2012/00614Capacitive ECG sensing in the NICU - design and results of the clinical feasibility study

Baby 1

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NICU| ECG relevance• 7 Dutch and 10 international NICUs (UK, Spain, Ireland, USA,

Belgium) responded to a survey we sent.• ECG an important tool for screening: 90% of participants check it

regularly whereas 10% of participants check it only once in a while.

• In order of importance: HR, HR variation, Respiration rate, QRS shape variation.

• Instantaneous heart rate (iHR) an important parameter for Sepsis detection1. Sepsis is the most common cause of death for infants beyond 1 week of age.

1. Early non invasive diagnosis of sepsis in preterm infants (Griffin Ped Research 2003; Griffin Pediatrics 2005; Moorman IEEE 2006, Fairchild 2012).

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Other players| Benchmarking

1. Eilebrecht et al. Cardiovascular Engineering and Technology 2012.2. Eilebreacht et al. Automobiltechnische Zeitschrift ATZ, 2011.3. Rasenack et al. Clinical Research in Cardiology 2012.4. Oehler et al. Phys. Measurement 2008.

Novelty Aspects

Adaptive framework that can deal with motion and artefacts

Unobtrusive embedding with no direct contact

Neonatal monitoring

Strong IP position

3 4

1, 2

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What can we do with instantaneous heart rate?

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Detection of neonatal sepsis using heart rate characteristics

Background

• Late-onset sepsis (onset > 72 hr after birth): 30% of preterm very low birth weight infants experience sepsis during their NICU stay (Stoll 2002)

• Sepsis is the most common cause of death among preterm infants beyond the first week of life.

• Heart rate characteristics monitoring (e.g changes in heart rate pattern) have shown to aid in the early non invasive diagnosis of sepsis in preterm infants (Griffin Ped Research 2003; Griffin Pediatrics 2005; Moorman IEEE 2006).

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Griffin Pediatrics 2001Kovatchev Ped Research 2003

Healthy infant

Septic infant

loss of variability & increase of transient decelerations, not exceeding alarm limits!

Detection of neonatal sepsis using heart rate characteristics

Background

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• The HRCi is derived from regression modeling and uses measures of standard deviation (SD), sample symmetry (R1 and R2), and SampEn to estimate the risk of upcoming sepsis and sepsis-like illness.

• The formula for the HRC index is: HRCi = [exp(A) / 1+exp(A)]where: A = intercept + β1(SD) + β2(R1) + β3(R2) + β4(SampEn)

• The intercept and coefficients β are estimated from epidemiologic data on sepsis and sepsis-like illness in the NICU (training set)

Detection of neonatal sepsis using heart rate characteristics

Algorithm

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HRCi percentiles correlate with risk for sepsis. Patients are classified into 3 risk categories. Low risk is defined as HRCi < 75th percentile (score <1). Medium risk (light gray boxes) includes infants with HRCi in the 75th to 90th percentile (score 1–2). The highrisk HRC group (dark gray box) has HRCi greater than 90th percentile (score >3).

Reference: Griffin Pediatrics 2005

Detection of neonatal sepsis using heart rate characteristics

HRCi as relative risk

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Increase of HRCi 24 hr before blood culture & start of antibiotics

Detection of neonatal sepsis using heart rate characteristics

Example

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In conclusion…

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Conclusion

• Neonates are a very vulnerable population. Research in this area could benefit a lot from:– Unobtrusive and pervasive sensor systems.– Support for neonatal comfort, sleep and growth– Intelligent solutions using the data acquired for

early prediction of deterioration.– Support for nurses and clinicians for more

efficient and easier care.

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Fulfilling our ambitions in Mother and Child CareHolistic comprehensive portfolio

Incubatorsand warmers

OB Ultrasound

NeonatalRespiratory

Support

Fetal and maternal

monitoring

Neonatal patient monitoring

Feeding and

Specialtyproducts

Developmental Care Positioningaids

AventHome apnea monitoring

Jaundice diagnostic and therapy

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People centered designHow we work

Research Onsite observation, shadowing, stakeholder interviews

AnalysisUnderstand workflows & issues Uncover insights & opportunities

Concept creation New materials, manufacturing & marketing feasibility

Validation with clinical experts, clinical trials with end users

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Acknowledgments | The teamCollaborators

• Wei Chen- TU/e

• Loe Feijs-TU/e

• Misha Croes-TU/e

• Dominika Potuzakova-TU/e

• Joanna Pilarczyk-TU/e

• Chris Nederhorst-RHF

• Hugo Zijlmans- AME

• Jos Bax (PINS)

• Mark Bogers (PINS)

Team

• Mohammed Meftah – Philips Research

• Martijn Schellekens- Philips Research

• Aline Serteyn- TU/e

• Rik Vullings-TU/e

• Jan Bergmans –TU/e

• Sidarto Bambang Oetomo- MMC/TU/e

• Astrid Osagiator-MMC

• Edwin Bongers-Philips Research

• Eefje Arts-Hornix- Philips Research

• Marjolein van Lieshout-Philips Research

• Vanessa Sattele-Philips Design

• Anton Janssen-Philips Research

Philips Business

• Siegfried Kaestle

• Amy Phillips

• Leslie Altimier

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