Full-body interface pressure testing as a method for performance evaluation of clinical support surfaces

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 Britain 0003—6870/98 $19.00#0.00

Full-body interface pressure testing as a method for performance evaluation of clinical support surfaces Frederick Shelton*, Richard Barnett and Eric Meyer Hill-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 their efforts to produce better clinical support surfaces that will reduce the incidence of pressure ulcers. In this study, a Pressure Index (Pindex) is defined which is derived from an analytical equation used to evaluate the average interface pressure, the peak pressure, the magnitude of the peak pressure, and the number of peak pressures on the entire body. The type of subjects needed to represent a population of users as well as the head of bed elevations necessary to simulate clinical applications were integrated with the Pindex to create a single-value mean pressure index which can be used to evaluate any type of surface. To determine the accuracy and repeatability of the mean pressure index, three surfaces (a standard hospital innerspring, a replacement foam mattress, and a lowairloss surface) were tested and evaluated using this method. The low airloss performed the best and the standard innerspring clearly performed the worst (p(0.0001). The method appeared to accurately and reproducibly predict the relative performance of the three surfaces in reducing pressure. ( 1998 Elsevier Science Ltd. All rights reserved. Keywords: pressure ulcer; decubitus ulcer; interface pressure.

Introduction

pressure measurement (Ferguson-Pell and Cardi, 1993; Nicol and Henning, 1976; Ferguson-Pell et al, 1976). Several different sensor technologies exist for the measurement of interface pressure, each with its particular performance characteristics. However, there are several common critical parameters of interface pressure including the overall size, the flexibility, the resolution, the accuracy, and the repeatability. Each of these parameters will affect the reliability of collected data. The type of data used in the evaluation of performance is equally important as the reliability of the data. The most commonly reported data is single value maximum pressures recorded at several ‘critical’ areas of the body. These maximum pressures are useful data, but they do not give any indication of the number of peak pressures, the overall size of the pressure peaks, the average pressure on the entire body, or even maximum peak pressures in locations of the body not considered ‘critical’. Therefore, a single repeatable indicator of interface pressure performance that accounts for the magnitude, number and size of all pressure peaks as well as the overall average pressure on the body is necessary to compare support surfaces. When reviewing the data of different support surfaces, the boundary conditions of the test have practical importance. Typically, the interface pressure data reported are collected with the subject in the supine position (0° head of bed elevation), using a very limited sample size,

Ten percent of all acute care patients in the US (Barczak et al, 1997) and 12% in Europe (O’Dea, 1995) suffer from pressure ulcers (decubitus ulcers, bed sores) on any given day. More than half of these patients are over the age of 65. Pressure ulcers are painful for patients and can be very costly to treat. Efforts to reduce the rate of occurrence have mainly been focused on prevention of hospital acquired pressure ulcers. One preventative approach has been through the improvement 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 to determine the performance of clinical support surfaces is required for the design of better surfaces and the interpretation of clinical outcomes. Designers have generally relied upon incomplete anthropometric data and subjective data from patients and clinicians to estimate performance. Interface pressure, the loading between a patient’s skin and the support surface, can be used to determine relative differences in support surface performance (Burman, 1993). Clinicians and researchers have raised numerous concerns about the use of different methods of interface

*Author to whom correspondence should be addressed 491

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and with an inadequate representation of the relevant population. The head elevation of the bed has a great impact on performance since it changes the weight distribution on the support surface. A range of head of bed elevations from 0 to 45° would best represent the common positions utilized in the clinical setting. Support surfaces are used by a wide range of patients differing in height, weight, morbidity, etc., all of which will affect support surface performance. Since interface pressure results are highly dependent on the particular measurement system used, the test subjects, the head of bed elevations, the testing environment, and the test procedure, it is incorrect to compare maximum pressure values or any data values from sources that do not have consistent equipment and test methods. Many researchers believe that interface pressure data should only be used for relative judgments between surfaces tested under the same conditions (Krouskop, 1990; Mclean, 1993). The system and standardized method detailed here can reliably and repeatably measure all the interface pressure characteristics, while adequately representing the desired population, allowing for realistic patient positioning and, using a purely mathematical and statistical method to evaluate these surfaces.

Methods Subjects Interface pressure measurements are highly sensitive to subject variability and the method of subject placement. No two humans, even of the same weight and stature, are anatomically identical, therefore interface pressure data taken on humans can vary significantly from person to person and even from test to test. The method used to place the subject on the surface and any movement of the subject will also directly influence the interface pressure data. The test method in this study utilized anthropometrically correct mannequins to minimize subject variability and standardize method of subject placement. The mannequins adequately represented at least 90% of the elderly (65—74 y old) US population. Statistical data were obtained from the US Department of Health and Human Services (US Department of Health and Human Services, 1976). From these data the height and weight of the desired range of people in the US was determined. A 5th percentile female was determined as the smallest body type at 4@10A (1.5 m) and 104 lb (47.2 kg). A 95th percentile male was determined as the largest body type at 6@0@@ (1.8 m) and 213 lb. (96.6 kg). Finally, a 50th percentile mannequin was determined using the median height and weight and a female body type, which represents the middle body type of the overall range, at 5@2@@ (1.6 m) and 135 lb. (61.2 kg). Using the body height and weight as independent variables, regression equations from two US Air Force studies (Young et al, 1983; McConille et al, 1980) were used to estimate the physical dimensions and weights of the individual segments of the body. The mannequins were constructed using the weight and dimension data from the regression equations for each of the 17 body segments. Each segment was weighed several times throughout the construction process to verify that it was correct. The mannequins consisted of a wooden shell with a steel skeletal system. The joints were created to mimic

the human range of motion. For simplicity the motion of the head was limited to flexion/extension, no rotation was allowed. Also no medial/lateral rotation of the leg or pronation/supination motion of the arm was accounted for. The motion of the spine was also limited to flexion/ extension, no medial/lateral motion was allowed. The spinal column was constructed of five interlocking ‘Y’shaped pin joints in order to simulate the flexibility of the human spine. The shoulder and hip joints were simulated using ball joints, while the ankle, knee, elbow, and neck were simulated using hinge joints. The joints of each mannequin do limit the overall range of motion, but not the range of motion necessary to achieve the various positions tested (0, 30, and 45° head of bed elevation). The mannequins were then covered with a thin layer of latex foam and polyurethane coated fabric. The foam and fabric were designed to simulate skin and subcutaneous fat layers while not introducing any time-dependent properties to the mannequin. 2.2. Head of bed elevations Interface pressure measurements were taken at three elevations of the head section of the bed, 0, 30, and 45°. The 0° head of bed elevation was chosen because it reflects the supine position, most commonly used in the hospital for critically injured or ill patients. The 30° head of bed elevation was chosen because it represents a typical head of bed elevation caregivers place patients in during their recovery to promote clearing of the lungs and aid in healing. Finally, the 45° head of bed elevation was chosen because it is the highest head of bed elevation patients usually used in recovery activities (i.e. eating, watching television, etc.). The beds were raised to this position using standard operating mode which also articulates the knee section of the bed as the head is elevated. Gantries were constructed to allow the testing personnel to pre-position the mannequins in the appropriate positions. It was also important that the mannequin’s body not be drawn across the surface during loading, since this will introduce non-normal forces. The positions were designed to allow all body parts of the mannequin to contact the surface approximately at the same time, therefore minimizing non-normal loading of the skin of the mannequin. The gantries also allow the reproducible placement of the mannequins in the same position for every test. During the collection of data the gantries did not carry any of the weight of the mannequin. Surfaces Three surfaces were chosen to represent the full range of surfaces seen in a hospital setting. A standard hospital mattress (an innerspring mattress) was chosen as a common rigid support surface used in hospitals. A low-airloss surface was chosen as one of the most compliant surfaces used in hospitals. One of the better solid foam replacement mattresses was also chosen to represent an expected performance somewhere between the two extremes. Measurement device We considered five different systems of several different technologies. A full body, interface pressure system (Tekscan 5315 system, Boston, MA) was finally chosen to

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

measure pressure for each support surface. The Tekscan system is a resistive ink system that measures the reduction of resistance for each sensor element due to loading of the element in the normal direction. The full-body system has more than 8000 sensing elements with a resolution of 0.4 in]0.4 in (10.2 mm]10.2 mm) across the entire set of four pads. The Tekscan system has some time dependent creep associated with its measurements, most of which occurs in the first 30 s after loading. Therefore, all data collection was done at 75 s after loading which allows the system to stabilize for better repeatability. Preliminary testing was conducted on the three surfaces to determine Tekscan’s accuracy and repeatability across the entire range of surfaces defined above. Two spherical and two cylindrical loading indentors (similar to body segment radii of the head and heel and thigh and buttock/back) were placed on the Tekscan system, on each surface. Four levels of increasing weight were placed in the indentors and the Tekscan system was used to verify the weights. Error was determined as a percent of measured weight from that of the known weight. The Tekscan sensor pads alone have at most, a 10% error in accuracy and less than a 5% error in repeatability across the entire range of radii, weights, and surfaces. However, because the entire system is based on a comparative analysis of surfaces, the primary source of error that will effect the results is repeatability. The entire system (the set of mannequins, and the procedure and analysis detailed here; which improves repeatability through more standardized comparisons) was tested and a 2% error in repeatability of the P was found. */$%9 Measurements Pressure index (Defined as an indexing of interface pressure). The P was calculated for each surface as well as */$%9 maximum heel and pelvis pressures. The P was cal*/$%9 culated using a standard mathematical equation intended to evaluate the closeness of a surface to that of the simplistic ideal surface (one with a homogeneously distributed pressure of 10 mmHg across the entire interface area, the ideal surface would consider tissue’s tolerances to load bearing) P "[(Mean !10)2#(Stdev )2]1@2. */$%9 10 10 Mean is the mean of all the active cells measuring 10 greater than or equal to 10 mmHg (1.3 kPa) and the Stdev is the standard deviation of all the active cells 10 measuring greater than or equal to 10 mmHg. Active cells under 10 mmHg were discounted to reduce bending error due to testing on conformal surfaces. The bending error on a conformal surface is of the order of 1—10 mmHg, while the data of 1—10 mmHg are not significant to skin blood flow. So in order to minimize bending effects while not significantly impacting the data, all cells under 10 mmHg were discounted. Maximum heel and pelvis pressures were determined by calculating the average pressure over a 1.6 in]1.6 in (4.1 cm]4.1 cm) area centered on the peak pressure measured in the region. The P includes in its analysis the peak loads (tradi*/$%9 tionally accepted to cause pressure ulcers) as well as the overall average loads. The average loads are included because the intensity of the pressure and duration of the pressure are the two contributing factors in pressure ulcer formation (i.e. a high homogeneous mean pressure over a long period could be as detrimental as a low mean pressure with high pressure peaks over a shorter period).

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Statistical analysis Means and standard deviations were calculated for the maximum pelvis and heel pressures and the P was */$%9 analyzed using multivariate analysis of variance (MANOVA) to determine the performance differences of each surface. The three mannequin types were defined as three levels of one variable for the overall comparison of performance. MANOVA was also used to compare the surfaces at each different head of bed elevation and for each mannequin body type. The least significant difference (LSD) method was used for post hoc comparisons. An alpha level of 0.05 was selected as the minimum level for significance. Three repetitions were run for each mannequin at each head of bed elevation and surfaces were randomized before each day of testing.

Results Interface pressure maps Figures 1—3 are typical interface pressure maps recorded during the test. Figure 1 shows the typical differences in interface pressure maps for the three mannequin types. The characteristic body curves unique to each of the different mannequin body types are evident from these maps. In Figure 2 one can see the differences in typical interface pressure maps for the standard hospital mattress, the foam replacement mattress, and the low-airloss surface. All three of these interface pressure maps were recorded using the 95th percentile mannequin at 0° head of bed elevation. The highest pressures are present on the most rigid surface (e.g. the standard hospital innerspring mattress) and the lowest pressures on the most conformal surface (e.g. the low-airloss surface). Figure 3 shows the typical interface pressure maps for the three head of bed elevations on the foam replacement mattress. Differences

Figure 1 Typical interface pressure maps of the 95th, 50th, and 5th percentile mannequins on a foam mattress at 0° head of bed elevation

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

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

Pressure index performance ¹able 1 shows the means and standard deviations of the P performance for each surface at each of the three */$%9 different head of bed elevations and for each of the three mannequin body types. MANOVA showed differences between the standard hospital mattress, the replacement foam mattress, and the low-airloss surface (F"317.6). MANOVA also showed differences in P with increas*/$%9 ing head of bed elevation (F"42.1) and for differing mannequin type (F"49.4). Small but significant interactions exist between each of the variables except between the surface type and the mannequin type. The power of the test was calculated at near 100%. LSD analysis showed that there were statistical differences between each of the three surface types (p(0.0001). LSD also showed statistical differences in mean P for each of */$%9 the different head of bed elevations (p(0.0004) and for each of the different mannequin types (p(0.002). The P values for the different surfaces, mannequins, and */$%9 head of bed elevations were summed to create three mean pressure indices. These mean pressure indices were created by summing across two of the three independent variables. The mean pressure indices data is plotted in Figures 4—6. Figure 4 shows a plot of the mean pressure indices for each mannequin type. The chart is an average of all head of bed elevations and surface types. Figure 5 is a plot of the mean pressure indices for each surface type. The plot is an average across all three head of bed elevations and across each of the three mannequin types. It shows that there was a dramatic difference in performance between the standard hospital mattress and the foam replacement mattress. The figure also showed that there was a less dramatic but still quite significant difference between the replacement foam mattress and the low-airloss surface. Figure 6 shows a plot of the mean pressure indices for each head of bed elevation. The P values are averaged across the three surface types */$%9 and the three mannequin types for this plot. Each increase in head of bed elevation produced a respective increase in the mean pressure index value.

Discussion Figure 3 Typical interface pressure maps of the 95th percentile mannequin at 0, 30, and 45° head of bed elevation on a replacement foam mattress

This method for performance evaluation of clinical support surfaces has certain limitations. The mannequins were designed to represent humans while removing the

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 bed elevation (deg)

5th percentile Mannequin

50th percentile Mannequin

95th Percentile Mannequin

Standard hospital mattress

0 30 45 0 30 45 0 30 45

17.1 20.7 17.0 9.5 11.2 13.6 8.2 8.4 11.2

20.0 20.7 22.3 12.5 16.3 15.3 9.9 10.8 15.9

18.2 20.3 22.0 11.2 13.1 16.3 9.8 9.7 13.6

Replacement foam mattress Low-airloss surface

(1.1) (0.8) (0.7) (1.6) (0.3) (3.4) (0.2) (0.8) (0.4)

(1.9) (0.9) (0.8) (0.7) (0.2) (1.0) (0.2) (0.7) (3.5)

(0.5) (1.3) (0.2) (0.1) (0.1) (0.3) (0.1) (0.4) (0.3)

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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 the mannequins there still remains some anatomically uncharacteristic features. The mannequins possess a skeleton system modeled after the human skeleton; however, the outer wooden shell and foam covering of the mannequin are not as malleable as the muscular system of a human. The mannequin bodies were also broken into segments which would react similar to body segments of the human. Also each of the mannequin bodies was crafted to have typical body curves seen with human subjects of similar body type. While the joints of the mannequin were simplified which limited the overall range of motion of the mannequins, these simplifications do not limit the mannequins’ range of motion in the lying positions. The latex foam and polyurethane-coated fabric simulated many of the characteristics of human body tissue, but none of the non-linear time-dependent properties of human tissue. Second, regression equations were used to generate the required body types and these equations are representative of in-shape people in the military

not elderly populations in hospitals. As there is little information available on elderly body types, especially those which are hospitalized, an assumption was made that the exterior of the elderly body was similar to that of a younger in-shape person of similar height and weight. Where available, statistics characteristic of the elderly were used to verify the height, weight, and some body dimensions of the mannequins. The compared dimensions were within 5—10% of the characteristic elderly dimensions. Third, all direct interface pressure measurement devices violate the interface which is being measured. The sensor pads were however designed to minimize this artifact, and made as flexible as possible to minimize the ‘hammocking’ effect. The pads were also made as thin as possible to minimize force redistribution due to the pads themselves. The pads were tested using known weights to determine the magnitude of the error they measured. The magnitude of the system error was determined to be 2% error in surface comparisons for the range of surfaces tested here. However, the pressures

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

measured are produced using mannequins which are at best representative of humans, and therefore these pressures are not necessarily the pressures that human skin experience. Fourth, absolute interface pressure values are not directly related to the formation of pressure ulcers in a specific patient (Barnett and Ablarde, 1995, 1994; Frantz and Xakellis, 1989; Seiler and Staehelin, 1979). However, interface pressure as a relative measure can show improvements from one support surface to the next. With these limitations in mind this method of clinical support surface performance evaluation should reasonably predict the differences in interface pressure distribution on the range of surfaces tested. However, the type of comparison is critical to the reliability of the comparison. Each interface pressure map as a whole must be compared for a complete understanding of support surfaces. When viewing interface pressure maps, like those seen in Figures 1—3, there are several things to keep in mind. The red is very important in comparing the surfaces because it shows the peak pressures acting on the subject; however, the differences in yellows, greens, and blues are also important. These other colors and the gradients of these colors show additional information on the support surface such as average pressure on the subject, distributed loads and their locations. These are important since the relationship between the duration and the extent of pressure-induced insufficiency of blood flow on the occurrence of pressure ulcers is inverse and follows a parabolic curve (Barnett and Ablarde, 1995). This indicates that moderately high pressures for a long period of time may be as damaging as high pressures for short periods of time. These smaller pressure gradients are left out when only maximum peak pressures are reported. As support systems become more complex and the designers begin to use interface pressure maps to optimize their systems, the peaks will begin to be replaced by lower more distributed loads over larger areas only noticeable when full-body

mapping is used. Furthermore, some analytical method of evaluation is crucial for a true comparison of interface pressure maps. While there is value in viewing interface pressure maps to determine the typical location and magnitudes of pressure on the subject, the comparison of support surfaces should be done mathematically and statistically. When using interface pressure maps to evaluate support surfaces, typical examples of the entire population for which the surface is designed to operate must be included in the analysis. For example, if a surface is optimized 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 surface will operate for a range of different body types is to test it using a range of body types. Likewise, the only way to evaluate how a surface will operate under normal usage is to test it under comparable boundary conditions (i.e. a range of head of bed elevations). This would also create a range of peak pressures or a mean pressure index which averages the characteristics of the surface across the whole range of subjects tested. There are several different challenges with reporting peak pressures. First, every measurement device has an error associated with its measurement. For these sensor pads it is at most 10%. The results in ¹able 2 show that the peak pressures are also highly dependent upon the body type and the head elevation of the bed. In addition, peak pressures in themselves do not indicate what pressures are being experienced a few centimeters away from the peak. Also, systems with poor resolution can miss peaks all together if the peak occurs between sensor elements. Commonly, a surface’s performance has been measured solely on single values of ‘peak’ interface pressure in some ‘critical’ regions (i.e. the sacrum, heels, etc.). We do not believe that these single peak pressures are necessarily representative of the performance of the entire surface nor of the entire population for which the

Performance evaluation of clinical support surfaces: F. Shelton et al. Table 2 Mean peak pressures for the different mannequins at 0, 30, and 45°° head of bed elevation for the standard hospital mattress. Measurements are in mmHg (in kPa) Head of bed Elevation (deg)

5th percentile mannequin

50th percentile mannequin

95th percentile mannequin

0 30 45

37.5 [5.0] 50.1 [6.7] 54.3 [7.2]

49.3 [6.6] 36.2 [4.8] 32.5 [4.3]

47.0 [6.3] 30.9 [4.1] 30.6 [4.1]

surface will be used. Publication of peak pressure results could therefore lead readers to develop incomplete conclusions. It is for these reasons that the investigators of this paper have chosen not to rely solely on peak pressure in the comparison of these surfaces. In Figure 4 one can see that each mannequin type produced a characteristic mean pressure indices when evaluated across the three support surfaces at all three angles of head of bed elevation. This was not a linear relationship based on the overall size of the mannequin, as one might have expected. This is most likely due to the structural differences in the exterior curves of the mannequin body types. Each body type has characteristic body curves which create unique interface pressure peaks and these characteristics are not merely based on height and weight but more on anatomic differences in curvatures of each body segment (the radius of the thigh, the circumference of the back, etc.). The mean pressure indices data shown in Figure 5 correlates with the clinical performance of each surface (Berman, 1993; Krouskop, 1990; McLean, 1993; Ferrel et al, 1993). The rigid innerspring mattress produces more pressure ulcers than the replacement foam mattress. The low-airloss surface produces the least amount of pressure ulcers (Ferrel et al, 1993). The increase in mean pressure indices due to the elevations of the head of the bed, seen in Figure 6, also follows what one would have expected since there are large increases in interface pressure in the pelvic region due to the proportionate redistribution of weight in this region. The pelvic region is the most frequent anatomic location of pressure ulcers (O’Dea, 1995). Because of this, most clinical practice guidelines include strict limitations on durations the head of the bed can be elevated. A mean pressure index for any surface can be calculated from interface pressure maps. The mean pressure index is based on the magnitude of the pressure, the number of pressure peaks, the size of the pressure peaks, and the average pressure placed on the body. The mean pressure indices includes the different loading conditions of 0, 30, and 45° head of bed elevation and the different body types of the desired population to create an overall performance characteristic value. The mean pressure indices could also be broken down to provide designers of new sleep surfaces with a detailed explanation of how their surface performs at any specific head of bed elev-

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ation or for any specific body type. This would allow designers to redesign their surfaces to perform optimally under the conditions and for the populations for which they are meant. To better characterize peaks in the pelvic or heel regions a similar P equation could be used to */$%9 evaluate each region independently as well as the overall mean pressure indices for the body. Questions remaining unanswered are: How well do the mannequins represent the human anatomy and kinematics of a human body lying on a support surface? What is the relationship between interface pressure and blood flow stasis? Interface pressure is only one of the factors which contributes to pressure ulcer formation, how can shear, maceration, and friction be reliably measured? These questions need to be answered with further research and will most definitely impact future technology development.

References Barczak, C., Barnett, R., Childs, E. and Bosley, L. (1997) ‘Fourth national pressure ulcer prevalence survey’. Adv wound care 10(4), 18—26 Barnett, R. and Ablarde, J. (1994) ‘Skin vascular reaction to standard patient positioning on a hospital mattress’ Adv ¼ound Care 7(1), 58—65 Barnett, R. and Ablarde, J. (1995) ‘Skin vascular reaction to short durations of normal seating’ Arch Phys Med Rehabil 76 : 533—540 Berman, P. (1993) ‘Using pressure measurements to evaluate different technologies’ Decubitus 6(3), 38—42 Ferguson-Pell, M., Bell F. and Evans, J. (1976) ‘Interface pressure sensors: existing devices, their suitability and limitations’ in Kenedi, R. and Cowden, J. (eds) Bedsore Biomechanics, Baltimore, University Park Press, pp 189—197 Ferguson-Pell, M. and Cardi, M. (1993) ‘Prototype development and comparative evaluation of wheelchair pressure mapping systems’ Assist Technol 5, 78—91 Ferrel, B., Osterweil, D. and Christenson, P. (1993) ‘A randomized trial of low-air-loss beds for treatment of pressure ulcers’ JAMA 269, 494—497 Frantz, R. and Xakellis, G. (1989) ‘Characteristics of skin blood flow over the Trochanter under constant, prolonged pressure’ Am J Phys Med Rehabil. 68(6), 272—276 Krouskop, T. (1990) Selecting a support surface’ Can E¹ J, 9, 5—14 McConille, J., Churchill, T., Kaleps, I., Clause, C. and Cuzzi, J. (1980) ‘Anthropometric relationships of body and body segment moments of inertia’ Air Force Aerospace Medical Research Laboratory McLean, J. (1983) Pressure reduction or pressure relief : making the right choice. J E¹ Nurs, 20, 211—215 Nicol, K. and Henning, E. (1976) ‘Time-dependent method for measuring 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 European countries J ¼ound Care 4, 192—195 Seiler, W. and Staehelin, H. (1979) ‘Skin oxygen tension as a function of imposed skin pressure: implication for decubitus ulcer formation’ J Amer Geriatrics Soc 27, 298—301 US Department of Health and Human Services (1976—1980) Vital and Health Statistics series 11 survey Young, J., Chandler, R., Snow, C., Robinette, K., Zehner, G. and Lofberg, M. (1983) ‘Anthropometric and mass distribution characteristics of the adult female’, Air Force Aerospace Research Laboratory