Evaluating Pressure Ulcer Development in Wheelchair-Bound Population Using Sitting Posture Identification

doi:10.4236/eng.2013.510B027

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Engineering, 2013, 5, 132-136

http://dx.doi.org/10.4236/eng.2013.510B027 Published Online October 2013 (http://www.scirp.org/journal/eng)

Evaluating Pressu re Ul cer D ev el o pm ent in

Wheelchair-Bound Population Using Sitting Posture

Identification

Farve Daneshvar Fard, Sahar Moghimi, Reza Lotfi

Depart ment of Ele ctrical Engineering, Biomedical Engineering Research Center,

Ferdowsi University of Mashhad, Mashhad, Iran

Email: f. [email protected], [email protected], [email protected]

Received February 2013

ABSTRACT

Pressure ulcers are a common complication among wheelchair-bound population. They are resulted from prolonged

exposure to high pressure, which restricts blood flow and leads to tissue necrosis. In this work, a continuous pressure

monitoring system is developed for pressure ulcer prevention. The system consists of 64 pressure sensors on a 40 × 50

cm2 sheet. Real time pressure data and corresponding maps are displayed on a computer simultaneously. Furthermore, a

posture detection procedure is proposed for sitting posture identification. Having information about the patient’s postur-

al history, caregivers are capable of a better decision about repo s itio ning and treating the patient.

Keywords: Interface Pressure Monitoring; Pressure Ulcer; Sitting Posture

1. Introduction

Sitting-acquired pressure ulcers are a common complica-

tion among wheelchair-bound population. It is reported

in literature that 36% to 50% of pressure sores are attri-

buted to sitting in a wheelchair [1]. Pressure ulcers are

resulted from prolonged exposure to high pressure,

which restricts blood flow and prevents blood from

bringing oxygen and nutrients to underlying tissues.

Hence, continuous measuring and monitoring of interface

pressure is the most useful approach for preventing pres-

sure ulcers, which are considered both a health and eco-

nomic problem as they cause excessive expenditures by

increasing the length of treatment up to several time s [ 2].

In spite of so many attempts for improving ulcer preven-

tion techniques, high incidence of pressure ulcers is ob-

served and more effective prevention methods are re-

quired [3-5].

The relationship between pressure intensity and dura-

tion is explored by Reswick and Roger [6]. High pres-

sures are tolerable for short times only and will lead to

tissue necrosis if they are unrelieved [7]. However, low

pressures are damaging if sustained for a lengthy period

of time [8]. Meffre, et al. [9] designed a particular type

of seat for wheelchair-bound patients using electro-pneu-

matic pressure sensors. These kinds of pressure sensors

are more expensive than capacitive and resistive sensors

and slower in data acquisition. Yip, et al. [10] presented

a flexible pressure monitoring system. The prototype

consists of 99 capacitive pressure sensors on a 17 × 22

cm2 sheet. Yang, et al. [11] designed and evaluated an

air-alternating wheelchair seat. They used resistive pres-

sure sensors for measuring interface pressure. Drennan

and Southard [12] presented a system consisting of pres-

sure sensitive pads. The system produces alarms if the

pressure intensity is more than the threshold adjusted by

the user.

In this paper, we present a system for continuous mon-

itoring of interface pressure. Furthermore, a procedure

for identifying different postures of sitting is proposed. A

wheelchair-bound patient may develop pressure ulcer if

he has no sensation in his buttock. Sore development

may happen faster if the patient’s trunk is tilted to one

side for a long period of time. In this work, we simulated

different sitting postures of a wheelchair-bound patient.

Having information about the patient’s postural history,

let caregivers decide better about repositioning and

treating the patient .

The remainder of this paper is structured as follows:

Section 2 describes the system design, including sensors

array setup as well as, circuit and software design. In

Section 3, we present the proposed procedure for sitting

posture identification. The proposed method is verified

by a particular statistical test. Conclusions are given in

Section 4.

F. D. FARD ET AL.

133

2. Methodology

2.1. Hardware Design of the System

In this work pressure sensing is carried out by Interlink

Electronics force sensing resistors (FSR-part no. 400),

which exhibit a decrease in resistance with an increase in

the force applied to the active surface. By measuring the

resistance, the applied force can be extracted and hence

the corresponding pressure value can be calculated. To

have a more precise measurement of force, each sensor

was calibrated before it was used. An array of sensors is

required for sensing pressure over a large area. We used

64 pressure sensors to cover an area of 30 × 40 cm2. Each

row of the array consists of 8 pressure sensors as illu-

strated in Figure 1. All sensors are fixed on a Plexiglas

sheet of size 40 × 50 cm2. A PCB of the same size was

designed for wiring the sensors and is fixed under the

Plexiglas sheet.

Measuring the resistances of FSR sensors is carried

out by an Atmel ATMEGA16 microcontroller analog-to-

digital converter. The same microcontroller controls

multiplexers to select one resistive sensor at any time

according to a particular sequence. The entire array of

the resistive sensors is scanned every 320 ms with a

sampling rate of 3 Hz.

A simplified schematic of the resistive sensors array

and the related electronic circuitry is shown in Figure 2.

Current source, designed by LM324 operational amplifi-

er and 2N3906 transistor, sources a current of 100 μA to

the selected resistor and the ADC measures the corres-

ponding value of voltage proportional to the resistance

value. Each sensor is placed in a serial connection with a

Figure 1. Pressure sensors array.

CD4067

...

To ADC

Control from

microcontroller

CD4067

To current

source

...

Figure 2. Schematic of resistive sensors array.

diode to prevent current flows into other sensors and as a

result creating undesirable routs. The designed PCB, il-

lustrated in Figure 3, interfaces the electronics and the

sensors sheet.

2.2. Software Design of the System

Digitized data of sensors are transmitted from the mi-

crocontroller to a computer via a USB interface using

FT232 chip. A GUI (Graphical User Interface) is devel-

oped in MATLAB to report pressure maps in real time,

retrieve previous maps and risks and set alarms. Post

processing of the obtained data is carried out in MAT-

LAB. Measured values of pressure of each sensor in the

array are saved in matrices at each sampling interval. In

the GUI, there is an option for the user to define two

thresholds for pressure intensity and duration. An alarm

can be created by the software if the pressure intensity of

one sensor is larger than the adjusted threshold and the

duration of that pressure is more than the time threshold.

This event is considered as a risky situation.

The GUI is designed in a way that we can see the last

risks and their occurrence times. This would also provide

useful information regard ing patient’s postural history. A

sample pressure map of a person sitting on the setup is

shown in Figure 4. The GUI stores the pressure in units

of mmHg for each sensor and MAT LAB post processing

is used to generate this pressure map.

3. Sitting Posture Identification

3.1. Experiment and Results

As it was mentioned before, developing sores may hap-

pen faster in a wheelchair-bound patient if he involunta-

Figure 3. PCB u sed for the electronics.

Figure 4. Pressure map of sitting volunteer.

F. D. FARD ET AL.

134

rily leans to one side for a long period of time. In this

work, we simulated different sitting postures of a wheel-

chair-bound patient. We had healthy volunteers in the

experiment and we defined four different postures for

them. These defined postures were assumed to simulate

sitting postures of a wheelchair-bound patient.

In the first defined posture, our subject sat straight on

the designed pressure sensitive seat with bent knees. This

was assumed to simulate proper sitting of a patient in a

wheelchair. In the second and third postures, the subject

sat with legs crossed, right on left and left on right re-

spectively. This was supposed to simulate the postures

during which a patient leans to his left and right sides. In

the last defined posture, the subject sat with legs

stretched. Figure 5 presents produced pressure maps for

different sitt i ng pos tures of the volunt e er.

3.2. Proposed Method for Identifying Sitting

Postures

Statistical parameters are used for detecting different

sitting postures. Values of mean, standard deviation,

skewness and kurtosis were calculated for each of the

produced maps shown in Figure 5. We used pressure

map matrices to calculate these parameters. Skewness

and kurtosis coefficients, related to each matrix, were

calculated from the probabilistic distribution of pressure

values in the middle rows of the matrix. Fitted distribu-

tions corresponding to each of pressure maps of Figu r e 5

are shown in Figure 6. As demonstrated, the result of

distribution fitting for posture 1 and 4 are close to stan-

dard normal distribution and therefore the corresponding

skewness values will be close to zero. Fitted distributions

for postures 2 and 3 result in negative and positive

skewness coefficients, respectively.

Now, we can present a method for detecting different

sitting postures according to the calculated parameters.

Skewness with negative sign (not close to zero) is an

indicator of the second posture. Skewness with positive

sign (not close to zero) is related to the third posture. The

first and last defined postures are identified by skewness

values close to zero (negative or positive). In addition,

we can distinguish the first posture from the last one us-

ing mean values, since the mean pressure value of the

total array in first posture is larger than that of the last

posture.

3.3. Verifying the Proposed Method

One way analysis of variance (ANOVA) was used to

verify the proposed method for identifying sitting post-

ures. The sitting posture identification experiment, de-

scribed in section 3.1, was performed for 5 volunteers (3

times for each subject), resulting in 15 different tests for

each of the four defined postures. We calculated mean,

standard deviation, skewness and kurtosis parameters for

these fifteen pressure matrices.

Figure 7 to Figure 10 represent the obtained box plots

for each parameter using MATLAB. Each column is re-

lated to one of the four defined postures. As it can be

seen in Figure 7, there is no overlap between mean val-

ues of posture 1 and posture 4. Therefore the mean val-

(a) (b)

Figure 5. Different sitting postures, (a) sitting straight with bent knees; (b) sitting straight with crossed legs, right on left; (c)

sitting straight with crossed legs, left on right; (d) sitting with stretch ed l eg s .

50 100 150 200 250

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mmHg

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mmHg

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mmHg

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mmHg

F. D. FARD ET AL.

135

(a) (b)

Figure 6. Fitted distributions for each posture of Figure 5 respectively.

Figure 7. Box plots for mean values.

Figure 8. Box plots for standard deviation values.

Figure 9. Box plots for skewness values.

Figure 10. Box plots for kurtosis values.

246810 12 14 16

0. 02

0. 04

0. 06

0. 08

0. 1

0. 12

Dat a

Density

fit norm al di stri but i on

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fit norm al di stri but i on

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1 2 34

Posture1 Posture2 Pos tur e3

P os tur e4

100

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350

12 3 4

P os ture 2

P os ture 3

P os ture 4

P os ture 1

-3

-2

-1

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P os tur e1

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1 2 34

P os ture 1

Posture2 P os tur e3

P os ture 4

F. D. FARD ET AL.

136

ues can be used for distinguishing these two postures.

Figu r e 8 shows that the values of standard deviation vary

from posture 1 to posture 4. According to Figure 9

skewness values of posture 2 have negative signs, and

skewness values of posture 3 have positive signs while

those of postures 1 and 4 are close to zero (negative or

positive). So these three groups (posture 2, posture 3,

posture 1 and 4) can be distinguished by the skewness

coefficient. Finally, Figure 10 shows that kurtosis coef-

ficients of posture 2 and 3 are generally larger than those

of postures 1 and 4. This sounds reasonable, since fitted

normal distributions of postures 1 and 4 are similar to

standard normal distribution, while those of postures 2

and 3 generally have higher peaks.

4. Conclusions

A continuous-time pressure monitoring system is pre-

sented. Due to its useful information about patient’s

movement history, feasibility for simultaneous monitor-

ing of pressure and alarming options, it is proposed that

this system can be utilized for pressure ulcer prevention.

Sitting posture identification is possible using the pre-

sented system. A method for detecting different sitting

postures has been proposed and verified. It is suggested

that preventing pressure ulcers in wheelchair-bound pa-

tients can be performed using the sitting posture detec-

tion method.

Spatial resolution of the designed system can be im-

proved in future works by increasing the number of

pressure sensors. The presented pressure monitoring sys-

tem can be expanded to be used in mattresses of bedrid-

den patients.

REFERENCES

[1] M. J. Geyer, D. M. Brienza, P. Karg, E. Trefler and S.

Kelsey, “A Randomized Control Trial to Evaluate Pres-

sure-Reducing Seat Cushions for Elderly Wheelchair Us-

ers,” Advances in Skin and Wound Care, Vol. 14, 2001,

pp. 120-129.

http://dx.doi.org/10.1097/00129334-200105000-00008

[2] T. S. Dharmarajan and J. T. Ugalino, “Pressure Ulcers:

Clinical Features and Management,” Journal of American

Medical Association, Vol. 296, 2006, pp. 974-984.

[3] M. Ferrarin, G. Andreoni and A Pedotti, “Comparative

Biomechanical Evaluation of Different Wheelchair Seat

Cushions,” Journal of Rehabilitation Research and De-

velopment, Vol. 37, 2000, pp. 315-324.

[4] D. M. Brienza, K. C. Chung, C. E. Brubaker, J. Wang, T.

E. Karg and C. T. Lin, “A System for the Analysis of Seat

Support Surfaces Using Surface Shape Control and Si-

multaneous Measurement of Applied Pressure,” IEEE

Transactions on Rehabilitation Engineering, Vol. 4, 1996,

pp. 103-113. http://dx.doi.org/10.1109/86.506407

[5] T. Defloor and M. H. Grypdonck, “Do Pressure Relief

Cushions Really Relieve Pressure?” Western Journal of

Nursing Research, Vol. 22, 2000, pp. 335-350.

http://dx.doi.org/10.1177/01939450022044458

[6] J. B. Reswick and J. E. Roger, “Experience at Rancho

Los Amigos Hospital with Devices and Techniques to

Prevent Pressure Sores,” In: Bedsore Biomechanics, Uni-

versity Park Press, Baltimore, 1976, pp. 301-310.

[7] I. Swain, “The Measurement of Interface Pressure,” In: D.

Bader, C. Bouten, D. Colin and C. Oomens, Eds., Pres-

sure Ulcer Research: Current and Future Perspectives,

Springer-Verlog, Berlin, 2005, p. 52.

[8] European Pressure Ulcer Advisory Panel (EPUAP) and

National Pressure Ulcer Advisory Panel (NPUAP) “Pres-

sure Ulcer Prevention, Quick Reference Guide,” 2009.

http://www.npuap.org

[9] R. Meffre, C. Gehin and A. Dittmar, “MAPI: Active In-

terface Pressure Sensor Integrated into a Seat,” Proceed-

ing of the 29th Annual International Conference of the

IEEE EMBS, 2007, pp. 1358-1361.

[10] M. Yip, D. Da He, E. winokur, A. G. Balderrama, R. She-

ridan and H. Ma, “A Flexible Pressure Monitoring Sys-

tem for Pressure Ulcer Prevention,” 31st Annual Interna-

tional Conference of the IEEE EMBS, 2009, pp. 1212-

1215.

[11] Y. Yang, J. Wang, Z. Gao and Y. Zhou, “Design and

Preliminary Evaluation of an Air-Alternating Wheelchair

Seating System for Pressure Ulcer Prevention,” Interna-

tional Conference on Bioinformatics and Biomedical

Technology, 2010, pp. 239-243.

[12] D. B. Drennan and D. W. Southard, “System and Method

of Reducing Risk and/or Severity of Pressure Ulcers,” US

Patent US2010/0268122 A1, 2010.