PII: S0003—6870(97)00069-0 Applied Ergonomics Vol. 29, No. 6, pp. 491—497, 1998( 1998 Elsevier Science Ltd

All rights reserved. Printed in Great Britain0003—6870/98 $19.00#0.00

Full-body interface pressure testing asa method for performance evaluation ofclinical support surfaces

Frederick Shelton*, Richard Barnett and Eric MeyerHill-Rom Co. Inc., 1069 State Rt 46E, Mail ¸ocation: J93, Batesville, IN, 47006, ºSA

(Received 19 October 1996; in revised form 10 September 1997)

A method for evaluating the performance of clinical support surfaces is required by designers in theirefforts to produce better clinical support surfaces that will reduce the incidence of pressure ulcers. Inthis study, a Pressure Index (Pindex) is defined which is derived from an analytical equation used toevaluate the average interface pressure, the peak pressure, the magnitude of the peak pressure, andthe number of peak pressures on the entire body. The type of subjects needed to representa population of users as well as the head of bed elevations necessary to simulate clinical applicationswere integrated with the Pindex to create a single-value mean pressure index which can be used toevaluate any type of surface. To determine the accuracy and repeatability of the mean pressureindex, three surfaces (a standard hospital innerspring, a replacement foam mattress, and a low-airloss surface) were tested and evaluated using this method. The low airloss performed the best andthe standard innerspring clearly performed the worst (p(0.0001). The method appeared toaccurately and reproducibly predict the relative performance of the three surfaces in reducingpressure. (( 1998 Elsevier Science Ltd. All rights reserved.

Keywords: pressure ulcer; decubitus ulcer; interface pressure.

Introduction

Ten percent of all acute care patients in the US (Barczaket al, 1997) and 12% in Europe (O’Dea, 1995) suffer frompressure ulcers (decubitus ulcers, bed sores) on any givenday. More than half of these patients are over the age of65. Pressure ulcers are painful for patients and can bevery costly to treat. Efforts to reduce the rate of occur-rence have mainly been focused on prevention of hospitalacquired pressure ulcers.

One preventative approach has been through the im-provement of clinical support surfaces (i.e. beds, tables,stretchers, chairs, etc.) that minimize external forces (i.e.pressure and shear) on a patient’s body. The ability todetermine the performance of clinical support surfaces isrequired for the design of better surfaces and the inter-pretation of clinical outcomes. Designers have generallyrelied upon incomplete anthropometric data and subjec-tive data from patients and clinicians to estimate perfor-mance.

Interface pressure, the loading between a patient’s skinand the support surface, can be used to determine relativedifferences in support surface performance (Burman,1993). Clinicians and researchers have raised numerousconcerns about the use of different methods of interface

*Author to whom correspondence should be addressed

pressure measurement (Ferguson-Pell and Cardi, 1993;Nicol and Henning, 1976; Ferguson-Pell et al, 1976).Several different sensor technologies exist for themeasurement of interface pressure, each with its particu-lar performance characteristics. However, there are sev-eral common critical parameters of interface pressureincluding the overall size, the flexibility, the resolution,the accuracy, and the repeatability. Each of these para-meters will affect the reliability of collected data. The typeof data used in the evaluation of performance is equallyimportant as the reliability of the data. The most com-monly reported data is single value maximum pressuresrecorded at several ‘critical’ areas of the body. Thesemaximum pressures are useful data, but they do not giveany indication of the number of peak pressures, theoverall size of the pressure peaks, the average pressure onthe entire body, or even maximum peak pressures inlocations of the body not considered ‘critical’. Therefore,a single repeatable indicator of interface pressure perfor-mance that accounts for the magnitude, number and sizeof all pressure peaks as well as the overall averagepressure on the body is necessary to compare supportsurfaces.

When reviewing the data of different support surfaces,the boundary conditions of the test have practical im-portance. Typically, the interface pressure data reportedare collected with the subject in the supine position (0°head of bed elevation), using a very limited sample size,

491

and with an inadequate representation of the relevantpopulation. The head elevation of the bed has a greatimpact on performance since it changes the weight distri-bution on the support surface. A range of head of bedelevations from 0 to 45° would best represent the com-mon positions utilized in the clinical setting. Supportsurfaces are used by a wide range of patients differing inheight, weight, morbidity, etc., all of which will affectsupport surface performance. Since interface pressureresults are highly dependent on the particular measure-ment system used, the test subjects, the head of bedelevations, the testing environment, and the test proced-ure, it is incorrect to compare maximum pressure valuesor any data values from sources that do not have consis-tent equipment and test methods. Many researchers be-lieve that interface pressure data should only be used forrelative judgments between surfaces tested under thesame conditions (Krouskop, 1990; Mclean, 1993).

The system and standardized method detailed here canreliably and repeatably measure all the interface pressurecharacteristics, while adequately representing the desiredpopulation, allowing for realistic patient positioning and,using a purely mathematical and statistical method toevaluate these surfaces.

Methods

Subjects

Interface pressure measurements are highly sensitive tosubject variability and the method of subject placement.No two humans, even of the same weight and stature, areanatomically identical, therefore interface pressure datataken on humans can vary significantly from person toperson and even from test to test. The method used toplace the subject on the surface and any movement of thesubject will also directly influence the interface pressuredata.

The test method in this study utilized anthropometri-cally correct mannequins to minimize subject variabilityand standardize method of subject placement. The man-nequins adequately represented at least 90% of the elder-ly (65—74 y old) US population. Statistical data wereobtained from the US Department of Health and HumanServices (US Department of Health and Human Services,1976). From these data the height and weight of thedesired range of people in the US was determined. A 5thpercentile female was determined as the smallest bodytype at 4@10A (1.5 m) and 104 lb (47.2 kg). A 95th percen-tile male was determined as the largest body type at 6@0@@(1.8 m) and 213 lb. (96.6 kg). Finally, a 50th percentilemannequin was determined using the median height andweight and a female body type, which represents themiddle body type of the overall range, at 5@2@@ (1.6 m) and135 lb. (61.2 kg). Using the body height and weight asindependent variables, regression equations from two USAir Force studies (Young et al, 1983; McConille et al,1980) were used to estimate the physical dimensions andweights of the individual segments of the body. Themannequins were constructed using the weight and di-mension data from the regression equations for each ofthe 17 body segments. Each segment was weighed severaltimes throughout the construction process to verify thatit was correct.

The mannequins consisted of a wooden shell witha steel skeletal system. The joints were created to mimic

the human range of motion. For simplicity the motion ofthe head was limited to flexion/extension, no rotationwas allowed. Also no medial/lateral rotation of the leg orpronation/supination motion of the arm was accountedfor. The motion of the spine was also limited to flexion/extension, no medial/lateral motion was allowed. Thespinal column was constructed of five interlocking ‘Y’-shaped pin joints in order to simulate the flexibility of thehuman spine. The shoulder and hip joints were simulatedusing ball joints, while the ankle, knee, elbow, and neckwere simulated using hinge joints. The joints of eachmannequin do limit the overall range of motion, but notthe range of motion necessary to achieve the variouspositions tested (0, 30, and 45° head of bed elevation).

The mannequins were then covered with a thin layer oflatex foam and polyurethane coated fabric. The foam andfabric were designed to simulate skin and subcutaneousfat layers while not introducing any time-dependentproperties to the mannequin.

2.2. Head of bed elevations

Interface pressure measurements were taken at threeelevations of the head section of the bed, 0, 30, and 45°.The 0° head of bed elevation was chosen because itreflects the supine position, most commonly used in thehospital for critically injured or ill patients. The 30° headof bed elevation was chosen because it represents a typi-cal head of bed elevation caregivers place patients induring their recovery to promote clearing of the lungsand aid in healing. Finally, the 45° head of bed elevationwas chosen because it is the highest head of bed elevationpatients usually used in recovery activities (i.e. eating,watching television, etc.). The beds were raised to thisposition using standard operating mode which also ar-ticulates the knee section of the bed as the head iselevated.

Gantries were constructed to allow the testing person-nel to pre-position the mannequins in the appropriatepositions. It was also important that the mannequin’sbody not be drawn across the surface during loading,since this will introduce non-normal forces. The positionswere designed to allow all body parts of the mannequinto contact the surface approximately at the same time,therefore minimizing non-normal loading of the skin ofthe mannequin. The gantries also allow the reproducibleplacement of the mannequins in the same position forevery test. During the collection of data the gantries didnot carry any of the weight of the mannequin.

Surfaces

Three surfaces were chosen to represent the full range ofsurfaces seen in a hospital setting. A standard hospitalmattress (an innerspring mattress) was chosen as a com-mon rigid support surface used in hospitals. A low-airlosssurface was chosen as one of the most compliant surfacesused in hospitals. One of the better solid foam replace-ment mattresses was also chosen to represent an expectedperformance somewhere between the two extremes.

Measurement device

We considered five different systems of several differenttechnologies. A full body, interface pressure system (Tek-scan 5315 system, Boston, MA) was finally chosen to

492 Performance evaluation of clinical support surfaces: F. Shelton et al.

measure pressure for each support surface. The Tekscansystem is a resistive ink system that measures the reduc-tion of resistance for each sensor element due to loadingof the element in the normal direction. The full-bodysystem has more than 8000 sensing elements with a re-solution of 0.4 in]0.4 in (10.2 mm]10.2 mm) across theentire set of four pads. The Tekscan system has some timedependent creep associated with its measurements, mostof which occurs in the first 30 s after loading. Therefore,all data collection was done at 75 s after loading whichallows the system to stabilize for better repeatability.

Preliminary testing was conducted on the three surfa-ces to determine Tekscan’s accuracy and repeatabilityacross the entire range of surfaces defined above. Twospherical and two cylindrical loading indentors (similarto body segment radii of the head and heel and thigh andbuttock/back) were placed on the Tekscan system, oneach surface. Four levels of increasing weight were placedin the indentors and the Tekscan system was used toverify the weights. Error was determined as a percent ofmeasured weight from that of the known weight. TheTekscan sensor pads alone have at most, a 10% error inaccuracy and less than a 5% error in repeatability acrossthe entire range of radii, weights, and surfaces. However,because the entire system is based on a comparativeanalysis of surfaces, the primary source of error that willeffect the results is repeatability. The entire system (theset of mannequins, and the procedure and analysis de-tailed here; which improves repeatability through morestandardized comparisons) was tested and a 2% error inrepeatability of the P

*/$%9was found.

Measurements

Pressure index (Defined as an indexing of interface pres-sure). The P

*/$%9was calculated for each surface as well as

maximum heel and pelvis pressures. The P*/$%9

was cal-culated using a standard mathematical equation int-ended to evaluate the closeness of a surface to that of thesimplistic ideal surface (one with a homogeneously dis-tributed pressure of 10 mmHg across the entire interfacearea, the ideal surface would consider tissue’s tolerancesto load bearing) P

*/$%9"[(Mean

10!10)2#(Stdev

10)2]1@2.

Mean10

is the mean of all the active cells measuringgreater than or equal to 10 mmHg (1.3 kPa) and theStdev

10is the standard deviation of all the active cells

measuring greater than or equal to 10 mmHg. Activecells under 10 mmHg were discounted to reduce bendingerror due to testing on conformal surfaces. The bendingerror on a conformal surface is of the order of1—10 mmHg, while the data of 1—10 mmHg are not signif-icant to skin blood flow. So in order to minimize bendingeffects while not significantly impacting the data, all cellsunder 10 mmHg were discounted. Maximum heel andpelvis pressures were determined by calculating the aver-age pressure over a 1.6 in]1.6 in (4.1 cm]4.1 cm) areacentered on the peak pressure measured in the region.The P

*/$%9includes in its analysis the peak loads (tradi-

tionally accepted to cause pressure ulcers) as well as theoverall average loads. The average loads are includedbecause the intensity of the pressure and duration of thepressure are the two contributing factors in pressureulcer formation (i.e. a high homogeneous mean pressureover a long period could be as detrimental as a low meanpressure with high pressure peaks over a shorter period).

Statistical analysis

Means and standard deviations were calculated for themaximum pelvis and heel pressures and the P

*/$%9was

analyzed using multivariate analysis of variance(MANOVA) to determine the performance differences ofeach surface. The three mannequin types were defined asthree levels of one variable for the overall comparison ofperformance. MANOVA was also used to compare thesurfaces at each different head of bed elevation and foreach mannequin body type. The least significant differ-ence (LSD) method was used for post hoc comparisons.An alpha level of 0.05 was selected as the minimum levelfor significance. Three repetitions were run for each man-nequin at each head of bed elevation and surfaces wererandomized before each day of testing.

Results

Interface pressure maps

Figures 1—3 are typical interface pressure maps recordedduring the test. Figure 1 shows the typical differences ininterface pressure maps for the three mannequin types.The characteristic body curves unique to each of thedifferent mannequin body types are evident from thesemaps. In Figure 2 one can see the differences in typicalinterface pressure maps for the standard hospital mat-tress, the foam replacement mattress, and the low-airlosssurface. All three of these interface pressure maps wererecorded using the 95th percentile mannequin at 0° headof bed elevation. The highest pressures are present on themost rigid surface (e.g. the standard hospital innerspringmattress) and the lowest pressures on the most conformalsurface (e.g. the low-airloss surface). Figure 3 shows thetypical interface pressure maps for the three head of bedelevations on the foam replacement mattress. Differences

Figure 1 Typical interface pressure maps of the 95th, 50th, and5th percentile mannequins on a foam mattress at 0° head of bedelevation

Performance evaluation of clinical support surfaces: F. Shelton et al. 493

Table 1 Pindex values for each support surface at every head of bed elevation and for each mannequin body type (standard deviation over 3 repetitions).

Support surface Head of bedelevation (deg)

5th percentileMannequin

50th percentileMannequin

95th PercentileMannequin

Standard hospital mattress 0 17.1 (1.1) 20.0 (1.9) 18.2 (0.5)30 20.7 (0.8) 20.7 (0.9) 20.3 (1.3)45 17.0 (0.7) 22.3 (0.8) 22.0 (0.2)

Replacement foam mattress 0 9.5 (1.6) 12.5 (0.7) 11.2 (0.1)30 11.2 (0.3) 16.3 (0.2) 13.1 (0.1)45 13.6 (3.4) 15.3 (1.0) 16.3 (0.3)

Low-airloss surface 0 8.2 (0.2) 9.9 (0.2) 9.8 (0.1)30 8.4 (0.8) 10.8 (0.7) 9.7 (0.4)45 11.2 (0.4) 15.9 (3.5) 13.6 (0.3)

Figure 2 Typical interface pressure maps for the 95th percentilemannequin on a standard hospital mattress, replacement foammattress, and low-airloss surface

Figure 3 Typical interface pressure maps of the 95th percentilemannequin at 0, 30, and 45° head of bed elevation on a replace-ment foam mattress

can be seen in the pelvic region with increasing head ofbed elevation.

Pressure index performance

¹able 1 shows the means and standard deviations of theP*/$%9

performance for each surface at each of the threedifferent head of bed elevations and for each of the threemannequin body types. MANOVA showed differencesbetween the standard hospital mattress, the replacementfoam mattress, and the low-airloss surface (F"317.6).MANOVA also showed differences in P

*/$%9with increas-

ing head of bed elevation (F"42.1) and for differingmannequin type (F"49.4). Small but significant interac-tions exist between each of the variables except betweenthe surface type and the mannequin type. The power ofthe test was calculated at near 100%. LSD analysisshowed that there were statistical differences betweeneach of the three surface types (p(0.0001). LSD alsoshowed statistical differences in mean P

*/$%9for each of

the different head of bed elevations (p(0.0004) and foreach of the different mannequin types (p(0.002). TheP*/$%9

values for the different surfaces, mannequins, andhead of bed elevations were summed to create three meanpressure indices. These mean pressure indices were cre-ated by summing across two of the three independentvariables. The mean pressure indices data is plotted inFigures 4—6. Figure 4 shows a plot of the mean pressureindices for each mannequin type. The chart is an averageof all head of bed elevations and surface types. Figure 5 isa plot of the mean pressure indices for each surface type.The plot is an average across all three head of bedelevations and across each of the three mannequin types.It shows that there was a dramatic difference in perfor-mance between the standard hospital mattress and thefoam replacement mattress. The figure also showed thatthere was a less dramatic but still quite significant differ-ence between the replacement foam mattress and thelow-airloss surface. Figure 6 shows a plot of the meanpressure indices for each head of bed elevation. TheP*/$%9

values are averaged across the three surface typesand the three mannequin types for this plot. Each in-crease in head of bed elevation produced a respectiveincrease in the mean pressure index value.

Discussion

This method for performance evaluation of clinical sup-port surfaces has certain limitations. The mannequinswere designed to represent humans while removing the

494 Performance evaluation of clinical support surfaces: F. Shelton et al.

Figure 4 Effect of mannequin type on mean pressure indices

Figure 5 Overall mean pressure indices for each surface type

variability created by human subjects. However, in themannequins there still remains some anatomically un-characteristic features. The mannequins possess a skel-eton system modeled after the human skeleton; however,the outer wooden shell and foam covering of the manne-quin are not as malleable as the muscular system ofa human. The mannequin bodies were also broken intosegments which would react similar to body segments ofthe human. Also each of the mannequin bodies wascrafted to have typical body curves seen with humansubjects of similar body type. While the joints of themannequin were simplified which limited the overallrange of motion of the mannequins, these simplificationsdo not limit the mannequins’ range of motion in the lyingpositions. The latex foam and polyurethane-coated fabricsimulated many of the characteristics of human bodytissue, but none of the non-linear time-dependent proper-ties of human tissue. Second, regression equations wereused to generate the required body types and these equa-tions are representative of in-shape people in the military

not elderly populations in hospitals. As there is littleinformation available on elderly body types, especiallythose which are hospitalized, an assumption was madethat the exterior of the elderly body was similar to that ofa younger in-shape person of similar height and weight.Where available, statistics characteristic of the elderlywere used to verify the height, weight, and some bodydimensions of the mannequins. The compared dimen-sions were within 5—10% of the characteristic elderlydimensions. Third, all direct interface pressure measure-ment devices violate the interface which is being meas-ured. The sensor pads were however designed tominimize this artifact, and made as flexible as possible tominimize the ‘hammocking’ effect. The pads were alsomade as thin as possible to minimize force redistributiondue to the pads themselves. The pads were tested usingknown weights to determine the magnitude of the errorthey measured. The magnitude of the system error wasdetermined to be 2% error in surface comparisons for therange of surfaces tested here. However, the pressures

Performance evaluation of clinical support surfaces: F. Shelton et al. 495

Figure 6 The mean pressure indices for each head of bed elevation

measured are produced using mannequins which are atbest representative of humans, and therefore these pres-sures are not necessarily the pressures that human skinexperience. Fourth, absolute interface pressure values arenot directly related to the formation of pressure ulcers ina specific patient (Barnett and Ablarde, 1995, 1994;Frantz and Xakellis, 1989; Seiler and Staehelin, 1979).However, interface pressure as a relative measure canshow improvements from one support surface to thenext. With these limitations in mind this method ofclinical support surface performance evaluation shouldreasonably predict the differences in interface pressuredistribution on the range of surfaces tested. However, thetype of comparison is critical to the reliability of thecomparison.

Each interface pressure map as a whole must be com-pared for a complete understanding of support surfaces.When viewing interface pressure maps, like those seen inFigures 1—3, there are several things to keep in mind. Thered is very important in comparing the surfaces becauseit shows the peak pressures acting on the subject; how-ever, the differences in yellows, greens, and blues are alsoimportant. These other colors and the gradients of thesecolors show additional information on the support sur-face such as average pressure on the subject, distributedloads and their locations. These are important since therelationship between the duration and the extent of pres-sure-induced insufficiency of blood flow on the occur-rence of pressure ulcers is inverse and follows a paraboliccurve (Barnett and Ablarde, 1995). This indicates thatmoderately high pressures for a long period of time maybe as damaging as high pressures for short periods oftime. These smaller pressure gradients are left out whenonly maximum peak pressures are reported. As supportsystems become more complex and the designers begin touse interface pressure maps to optimize their systems, thepeaks will begin to be replaced by lower more distributedloads over larger areas only noticeable when full-body

mapping is used. Furthermore, some analytical methodof evaluation is crucial for a true comparison of interfacepressure maps. While there is value in viewing interfacepressure maps to determine the typical location andmagnitudes of pressure on the subject, the comparison ofsupport surfaces should be done mathematically andstatistically.

When using interface pressure maps to evaluate sup-port surfaces, typical examples of the entire populationfor which the surface is designed to operate must beincluded in the analysis. For example, if a surface isoptimized to work for a 4@10@@ (1.5 m), 104 lb (47.2 kg)person it may not operate well for a 6@0@@ (1.8 m), 213 lb(96.6 kg) person. The only way to represent how a surfacewill operate for a range of different body types is to test itusing a range of body types. Likewise, the only way toevaluate how a surface will operate under normal usageis to test it under comparable boundary conditions (i.e.a range of head of bed elevations). This would also createa range of peak pressures or a mean pressure index whichaverages the characteristics of the surface across thewhole range of subjects tested.

There are several different challenges with reportingpeak pressures. First, every measurement device has anerror associated with its measurement. For these sensorpads it is at most 10%. The results in ¹able 2 show thatthe peak pressures are also highly dependent upon thebody type and the head elevation of the bed. In addition,peak pressures in themselves do not indicate what pres-sures are being experienced a few centimeters away fromthe peak. Also, systems with poor resolution can misspeaks all together if the peak occurs between sensorelements. Commonly, a surface’s performance has beenmeasured solely on single values of ‘peak’ interface pres-sure in some ‘critical’ regions (i.e. the sacrum, heels, etc.).We do not believe that these single peak pressures arenecessarily representative of the performance of the en-tire surface nor of the entire population for which the

496 Performance evaluation of clinical support surfaces: F. Shelton et al.

Table 2 Mean peak pressures for the different mannequins at 0, 30, and45°° head of bed elevation for the standard hospital mattress. Measure-ments are in mmHg (in kPa)

Head of bedElevation (deg)

5th percentilemannequin

50th percentilemannequin

95th percentilemannequin

0 37.5 [5.0] 49.3 [6.6] 47.0 [6.3]30 50.1 [6.7] 36.2 [4.8] 30.9 [4.1]45 54.3 [7.2] 32.5 [4.3] 30.6 [4.1]

surface will be used. Publication of peak pressure resultscould therefore lead readers to develop incomplete con-clusions. It is for these reasons that the investigators ofthis paper have chosen not to rely solely on peak pressurein the comparison of these surfaces.

In Figure 4 one can see that each mannequin typeproduced a characteristic mean pressure indices whenevaluated across the three support surfaces at all threeangles of head of bed elevation. This was not a linearrelationship based on the overall size of the mannequin,as one might have expected. This is most likely due to thestructural differences in the exterior curves of the manne-quin body types. Each body type has characteristic bodycurves which create unique interface pressure peaks andthese characteristics are not merely based on height andweight but more on anatomic differences in curvatures ofeach body segment (the radius of the thigh, the circumfer-ence of the back, etc.). The mean pressure indices datashown in Figure 5 correlates with the clinical perfor-mance of each surface (Berman, 1993; Krouskop, 1990;McLean, 1993; Ferrel et al, 1993). The rigid innerspringmattress produces more pressure ulcers than the replace-ment foam mattress. The low-airloss surface produces theleast amount of pressure ulcers (Ferrel et al, 1993). Theincrease in mean pressure indices due to the elevations ofthe head of the bed, seen in Figure 6, also follows whatone would have expected since there are large increases ininterface pressure in the pelvic region due to the propor-tionate redistribution of weight in this region. The pelvicregion is the most frequent anatomic location of pressureulcers (O’Dea, 1995). Because of this, most clinical prac-tice guidelines include strict limitations on durations thehead of the bed can be elevated.

A mean pressure index for any surface can be cal-culated from interface pressure maps. The mean pressureindex is based on the magnitude of the pressure, thenumber of pressure peaks, the size of the pressure peaks,and the average pressure placed on the body. The meanpressure indices includes the different loading conditionsof 0, 30, and 45° head of bed elevation and the differentbody types of the desired population to create an overallperformance characteristic value. The mean pressure in-dices could also be broken down to provide designers ofnew sleep surfaces with a detailed explanation of howtheir surface performs at any specific head of bed elev-

ation or for any specific body type. This would allowdesigners to redesign their surfaces to perform optimallyunder the conditions and for the populations for whichthey are meant. To better characterize peaks in the pelvicor heel regions a similar P

*/$%9equation could be used to

evaluate each region independently as well as the overallmean pressure indices for the body.

Questions remaining unanswered are: How well do themannequins represent the human anatomy and kin-ematics of a human body lying on a support surface?What is the relationship between interface pressure andblood flow stasis? Interface pressure is only one of thefactors which contributes to pressure ulcer formation,how can shear, maceration, and friction be reliably meas-ured? These questions need to be answered with furtherresearch and will most definitely impact future techno-logy development.

References

Barczak, C., Barnett, R., Childs, E. and Bosley, L. (1997) ‘Fourth nationalpressure ulcer prevalence survey’. Adv wound care 10(4), 18—26

Barnett, R. and Ablarde, J. (1994) ‘Skin vascular reaction to standardpatient positioning on a hospital mattress’ Adv ¼ound Care 7(1),58—65

Barnett, R. and Ablarde, J. (1995) ‘Skin vascular reaction to shortdurations of normal seating’ Arch Phys Med Rehabil 76 : 533—540

Berman, P. (1993) ‘Using pressure measurements to evaluate differenttechnologies’ Decubitus 6(3), 38—42

Ferguson-Pell, M., Bell F. and Evans, J. (1976) ‘Interface pressuresensors: existing devices, their suitability and limitations’ in Kenedi,R. and Cowden, J. (eds) Bedsore Biomechanics, Baltimore, Univer-sity Park Press, pp 189—197

Ferguson-Pell, M. and Cardi, M. (1993) ‘Prototype development andcomparative evaluation of wheelchair pressure mapping systems’Assist Technol 5, 78—91

Ferrel, B., Osterweil, D. and Christenson, P. (1993) ‘A randomized trialof low-air-loss beds for treatment of pressure ulcers’ JAMA 269,494—497

Frantz, R. and Xakellis, G. (1989) ‘Characteristics of skin blood flowover the Trochanter under constant, prolonged pressure’ Am J PhysMed Rehabil. 68(6), 272—276

Krouskop, T. (1990) Selecting a support surface’ Can E¹ J, 9, 5—14McConille, J., Churchill, T., Kaleps, I., Clause, C. and Cuzzi, J. (1980)

‘Anthropometric relationships of body and body segment momentsof inertia’ Air Force Aerospace Medical Research Laboratory

McLean, J. (1983) Pressure reduction or pressure relief : making theright choice. J E¹ Nurs, 20, 211—215

Nicol, K. and Henning, E. (1976) ‘Time-dependent method for measur-ing force distribution using a flexible mat as a capacitor’ in Komi, P.(ed.), Biomechanics University Park Press, Baltimore, pp 433—440

O’Dea, K. (1995) ‘The prevalence of pressure sores in four Europeancountries J ¼ound Care 4, 192—195

Seiler, W. and Staehelin, H. (1979) ‘Skin oxygen tension as a function ofimposed skin pressure: implication for decubitus ulcer formation’J Amer Geriatrics Soc 27, 298—301

US Department of Health and Human Services (1976—1980) Vital andHealth Statistics series 11 survey

Young, J., Chandler, R., Snow, C., Robinette, K., Zehner, G. and Lof-berg, M. (1983) ‘Anthropometric and mass distribution character-istics of the adult female’, Air Force Aerospace ResearchLaboratory

Performance evaluation of clinical support surfaces: F. Shelton et al. 497