Pilot Validation of a Computational Seated Human Model
Using an Instrumented Chair
C.G. Olesen1, M. de Zee1 and J. Rasmussen2
1
Department of Health Science and Technology, Aalborg University, Denmark
2
Department of Mechanical Engineering, Aalborg University, Denmark
e-mail: cgol03@hst.aau.dk
Abstract
Sitting-acquired deep tissue injuries (SADTI) are the most serious type of pressure ulcers. In order to
investigate the ethiology of SADTI a new approach is under development. A musculo-skeletal model
can predict forces at different seated positions and thereby find an optimum position where the risk of
SADTI is minimized. This study focuses on validation of a musculo-skeletal model developed in the
AnyBody Modeling System for predicting reaction forces on a wheelchair. A Wheelchair with forcemeasuring equipment was developed, an experiment was conducted, and the experimental results were
compared with the predictions of the computational model. The results show that the model predicted
changes in reaction forces due to changes in the chair posture well. It was concluded that the
experimental approach is satisfactory and more experiments should be carried out to completely
validate the computational model.
1.
INTRODUCTION
Pressure ulcers, more commonly known as
pressure sores, are a frequent complication to
spinal cord injury (SCI) patients. The disease can
have various ethiologies and is in general poorly
understood. The type of pressure sore we are
particularly interested in is the sitting acquired
deep tissue injury (SADTI) that wheel chair users,
i.e. paraplegic and quadriplegic patients are
susceptible to.
Statistics show that 24 % of all patients with SCI
experience a pressure ulcer during their
rehabilitation hospital stay [1]. It is also estimated
that 50-85% of all patients with SCI will
experience a pressure ulcer during their life time
[2]. These are very general prevalence’s that cover
all kinds of pressure ulcers; the deep tissue injury is
not the most common one, but certainly the worst.
The problem is that they can spread underneath the
skin and when they do so, they can be very difficult
to treat and in some cases they are lethal. [3].
The ethiology behind pressure ulcers in general and
specifically SADTI are poorly understood. A
number of main risk factors have been identified,
but to which degree these risk factors interact and
how they cause pressure sores for wheel chair users
should be investigated in greater detail.
It is well acknowledged that pressure sores are
primarily caused by sustained mechanical loading
of the soft tissues [4, 5]. The types of loading can
be described as pressure, pressure gradients and
shear forces [6]. These loads conspire in a
complicated fashion to generate stress states
varying from point to point in the soft tissues. An
understanding of the input loads is therefore the
first step towards a genuine understanding of
pressure sore formation.
The magnitude and position of the loads is
influenced by the patient’s posture and the support
conditions of the wheelchair, for instance what
cushion type is used, backrest angle, seat
inclination angle, foot rest height, arm rest height
and so on [6, 7].
1
by Gilsdorf et al. (1991)[7] on paraplegic and
quadriplegic patients, because the latter study
unlike the former used a wheelchair equipped with
armrests.
Experiment
conducted
Motion Data
Force Data
MatLab Script
Motion Data
Figure 1. The experimental setup with the wheelchair
mounted with the force measuring equipment. The
bright dots are the reflective markers.
A lot of the risk factors have been experimentally
investigated in combination, but it is difficult to
compare the results due to the variations between
subjects and the differences between the protocols
used. For instance, when Maurer and Sprigle
(2004)[8] studied how the seat inclination angle
and backrest angle affect the pressure in the
buttock area, they found no significant differences
in pressure. However, they did not look at the shear
forces or the pressure gradients and according to
[9] when shear is present it takes six times less
pressure to cause ulcerations. Others have shown
similar results on how pressure and shear causes
blood occlusions in the superficial tissue [10-12].
They all showed that pressure can cause occlusion
in the blood flow, but if shear is present it takes
less pressure to lower the blood flow. So shear
forces are important and perhaps even more so
when looking at how paraplegic patients sit.
Bennett et al. (1984)[13] saw higher shear stresses
in paraplegic patients than normal subjects during
sitting.
There are studies that describe experiments where
subjects have been seated on chairs and
wheelchairs with load cells and pressure mats. For
instance, Gilsdorf et al. (1990)[14] performed an
experiment where a force plate was used as a seat
in a wheel chair, and normal and shear forces were
measured for normal subjects while changing the
backrest angle. Their results are difficult to
compare with for example another result also done
Experimental
Force Data
Comparison of
forces
AnyBody
”Seated Human”
Estimated
Force Data
Figure 2.
Recording and
post processing of
experimental data using a Matlab script, transfer of
the motion data to the AnyBody model for simulation
of forces and finally comparison between measured
and simulated forces.
In some experiments conducted by Goossens et al.
(1997)[15] on healthy subjects the maximum shear
was found in areas where the pressure also was
highest but no relation between seat angles and
shear stress could be found, possibly because of the
influence of body posture.
Bennett et al. (1984)[13] developed a shear stress
sensor that also included pressure and blood flow
but it was developed as a hard sensor which was
not suitable for measuring in a soft cushion
environment. Measurements were therefore taken
on subjects sitting on wood surfaces. This study did
see larger shear stresses in paraplegic and
hospitalized geriatric patients than in normal
subjects and they measure larger blood flow in the
two latter groups. This indicates that paraplegic
patients have a higher than normal need to relieve
pressure from the buttock area.
2
All the aforementioned experiments contribute to
the understanding of forces between a seated
human and its environment, but differences in aims
and experimental protocols make them impossible
to compare. Consequently this study proposes that
a more analytical approach could contribute further
to understanding of how the seating posture affects
the mechanical loading of the soft tissue in the
buttock region. Such an understanding might also
benefit designers of automotive, airline and office
seats because of contribution of contact forces’ to
the perceived discomfort.
A validated analytical model could be used to
predict load values from different seating postures
without the need for costly experiments.
Furthermore, an analytical model is free from the
inevitable experimental noise and statistical
variations due to individual differences between
subjects and differences in protocols that may
otherwise occlude significant findings.
Before using any model it should be validated with
respect to the predicted forces [16]. Therefore the
objectives of this study is to validate a musculoskeletal model with respect to its ability to predict
reaction forces and how these change with a
change in the seated posture. This is accomplished
by comparing force predictions from a model with
measurements from test subjects.
2.
METHODS AND MATERIALS
The study design includes an experimental and a
modeling part. The experimental setup includes
measurements of reaction forces on a wheelchair
measured in synchronization with motion capture
data for recording of the sitting posture. A
musculo-skeletal model was created to mimic the
seated position and thereby estimate reaction forces
between the chair and the model. These reaction
forces could then be compared with the forces
measured during the experiment and in that way
validate the musculo-skeletal model.
Experimental Setup
Force measurements
A custom-built wheelchair, see Figure 1
(Wolturnus A/S, Nibe, Denmark) was mounted
with force-measuring equipment (Advanced
Mechanical Technology, Inc., Watertown, MA,
US). The chair was constructed by mounting an
OR6-7-1000 force plate as a seat, and as a footrest
an OR6-7-2000 force plate mounted in the floor
was used. The backrest consisted of two horizontal
bars mounted in each side to two multi-axis force
and torque transducers. In total, four multi-axis
force transducers (2 x FS6-250 & 2 x FS6-500)
were mounted in the two backrest bars. The
backrest bars were covered with 4 mm foam and
the seat was covered with a 2 mm rubber mat.
The wheelchair could be adjusted in a number of
ways, the inclination angle of the seat and backrest.
The seat could slide forward/backward. The
backrest bars could slide up/down and
forward/backwards. These adjustments meant that
the wheelchair could be adjusted into any posture
with respect to backrest height, seat dept, seat angle
and backrest angle.
The forces applied to the force plates and force
transducers were amplified using amplifiers from
the same manufacturer as the force measuring
equipment. The amplifiers were sampled using
Texas Instrument 16 bit A/D converters, connected
to a computer where sampled by Mr.Kick, a
software for data collecting (Mr.Kick, Aalborg
University, Aalborg, Denmark). Details about
Mr.Kick can be found at [17]. All six channels on
each force-measuring device were sampled giving
a total of 36 channels. The sampling rate was 20
Hz over 10 seconds giving 200 samples per
channel.
Posture Assessment
It is partially unknown how the chair adjustments
influence the posture of the occupant. Therefore the
posture of the subject had to be measured.
The chair positions were measured using a motion
capture system (Qualisys Proreflex 240,
Gothenburg, Sweden) with eight cameras. Passive
3
reflective markers were placed in each corner of
the two force plates and on both sides of the two
backrest bars seen in Figure 1
The posture of the subject sitting in the wheelchair
was also measured using passive reflective
markers. The markers were placed at the following
anatomical landmarks: Forehead, sternum,
shoulder, elbow, hand, pelvis, greater trochanter,
knee and ankles, which also can be seen in Figure
1. The positions of the markers were measured
with a sampling rate of 20 Hz over 10 seconds.
The force measurements and the motion capture
system were started by a trigger in order to
synchronize the force and motion capture
recordings.
Conducting the Experiment
One subject was included in the study. The subject
was 179 cm high and weighed 68 kg.
The subject height, mass and distance from floor to
rear side of the knee while seated were measured.
The latter distance was used as a guide for setting
of an appropriate seat height, i.e. the distance from
the footrest force plate to the front top edge of the
seat. This distance was kept constant throughout all
experiments. The subject was seated in the chair
and markers were placed at the anatomical
landmarks. The subject was instructed to sit in as
relaxed as possible with the arms crossed over the
chest. The force plates and load cells were reset
every time the posture of the chair was changed to
make sure that the baseline was the same for all
measurements. The experiment included 14
different seated postures each measured at least
twice to be sure that at least one measurement was
ok. The 14 different postures varied in seat angle,
backrest height and backrest angle. Between each
of the postures only one parameter was changed
and the subject sat at the chair 4 min between each
experiment, to ensure that the seated position had
reached a steady state as described by Crawford,
S.A. et. al. (2005) [18]. It was realized during the
post processing that not all the 14 experiments
were of any particular interest for the study because
they included repetitions. Consequently only 11 of
them were used for validation purposes.
Post Processing
Motion Capture
The motion capture data from the Qualisys cameras
was first post processed in QTM (Qualisys
Tracking Manager V.1.10.282) were the markers
were identified and named. The markers were then
exported to a TSV file (Tab Separated Values).
Table 1 shows the most important in- and output
parameters to the AnyBody model
Input Parameters
Output Parameters
Seat Angle
Backrest normal force
Backrest Angle
Seat normal force
Height of Backrest
Seat shear force
Distance between Footrest normal force
backrest bars
Subject posture
Footrest shear force
The TSV file was then processed using a custom
made Matlab (MatLab R2007B, Mathworks Inc.,
Ma, US.) script that calculated the angles and
positions between the seat, backrest bars, and
footrest. A relative origin was also calculated as the
where an extension to the line between the two
backrests in the right side intersected with the seat.
The markers placed at the bony landmarks at the
subject were calculated relatively to the calculated
origin. The output of the Matlab scripts was a text
file that could be included in the AnyBody model.
The text file consisted of all the marker positions
for driving the model. For an overview of the
process, see Figure 2.
Force Data
The collected force data was gathered using Mr.
Kick which saves each data file as a Matlab data
file. A script was used for averaging the values. A
Matlab script combined the motion capture data
with the measured forces, and the center of mass
4
(COM) for the subject was calculated based on the
normal and shear forces from the force plates and
load cells.
AnyBody Modeling
The modeling was done using the AnyBody
modeling system (AnyBody Technology A/S,
Aalborg, Denmark). The model used was the
“Seated Human” from the public domain AnyBody
model repository [19], described in [20]. The
AnyBody Modeling System is computer software
designed for constructing musculo-skeletal models
of the human body and its environment and for
determining how interact. The mathematic and
mechanical theories behind were described in [21].
wheelchair. The seated model relies on a set of
assumptions described in [20]. In addition, a few
assumptions were made about the interface
between the chair and the human body:
Table 2 shows an experiment that was conducted
three times. The forces for each of the three
measuments and the mean and standard deviation.
This illustrates a small variation. BT: backrest top,
BB: backrest bottom, S: seat, FR: footrest.
Forces
1.exp 2.exp 3.exp Mean Std
BT(Fs)
5,4
4,5
5,6
5,2
0,59
BT(Fn)
18,2
21,3
22,5
20,7
2,2
BB(Fs)
4,6
2,7
1,1
2,8
1,7
15,0
13,2
16,4
4,1
BB(Fn) 21,0
Figure 3 shows to the left the anybody model in the
seated position driven by the data recorded with the
Qualisys motion capture system. To the right a close
up of the backrest support, where shown a posture
only supported by the upper backrest. The backrests
are the two squares. The lines originating from the
spine indicates the normal force.
The AnyBody model was altered to fit the
experiment. First the model was scaled in weight to
the body mass if the test subject, i.e. 68 kg. The
subject
was
approximately
the
same
anthropometrical size as the AnyBody model,
which is based on a 50th percentile male.
The model consists of two parts: A human model
and an environment model representing the
S(Fn)
585,8 590,0 585,1 587,0
2,7
S(Fs)
11,7
10,1
9,0
10,3
1,4
FR(Fn)
88,1
86,0
91,7
88,6
2,9
FR(Fs)
20,7
16,0
17,3
18,0
2,4
The friction coefficients µ, between the body and
the seat and footrest was estimated to µ=0.5
because the surface material was rubber. For the
backrest µ=0 was used because the foam could
rotate around the backrest bars.
The model is illustrated in Figure 3 where the model
sits in the chair in the same position as in Figure 1.
The armrest, legrest, and head rest were removed
from the original model since they were not present
in the wheelchair used in the experiment. The
backrest was changed to be two independent
backrest bars as it was in the experiment. The size
and position of the seat, backrest bars and footrest
were set and driven by the input file generated by
the Matlab scripts.
The human model was driven by the markers
recorded during the experiment such that the
5
posture of the human body in the model
corresponds to the experiment.
The connection between the chair and the human
model was modeled as contact elements
perpendicular to the contact surfaces and capable
of taking Coulomb friction into account.
weight of 681 N. The subject weight was
calculated from the reaction forces on the chair,
and the mean was also 681 N with a SD of 8 N.
In Table 2 the measured results from a single
experiment are presented. The forces for three
measurements conducted at the same experiment.
Comparison
Effect of changing the backrest height
The comparison between the experimentally
obtained forces and the estimated forces from the
AnyBody model was done by comparing absolute
force values and trends when changing an input
parameter. The force values were plotted as a
function of the parameter that was changed.
The first set of experiments that were conducted
investigated the effect of changing the height of the
backrest bars, when the seat was horizontal and the
backrest vertical. The heights of both bars were
changed 5 times between the first 6 experiments.
The result presented in Figure 5 shows the summed
normal force (Fn) in the two backrests as a function
of the average height. The figure shows that the
trends for the AnyBody model and the experiment
were the same, but there was an offset difference.
The two results agree that raising the backrest bars
cause the normal force applied to them to
decreased. There was an offset of approximately 30
N.
The parameters that were used for the comparison
could be split into input and output parameters. The
input and output parameters are listed in Table 1.
3.
RESULTS
The results from forces measured during the
experiment and estimated forces from the
AnyBody model were compared as absolute values
and trends while changing one parameter at the
time.
Backrest Fn as a Function of Backrest Height
80
70
700
Experimental
AnyBody
695
50
40
690
Weight / N
Fn / N
60
The weight of the model and the subject
685
30
680
20
0.24
675
0.26
0.28
0.3
0.32
0.34
0.36
0.38
0.4
0.42
Avg. Height / m
670
Figure 5. The normal force on the backrests plotted
against the backrest average height
665
660
Fn - AnyBody
Fn - Experimental
LinReg Fn - AnyBody
LinReg Fn - Experimental
2
4
6
8
10
12
14
Experiment Number
Figure 4. Weight of the subject in 14 experiments
measured as the sum of vertical forces on the
dynamometers.
The first result calculated was the absolute weight
of model and subject for each of the 14
experiments conducted. The result is depicted
around the weight of the AnyBody model which is
illustrated as a straight line due to the constant
The pattern created by the samples should be
noticed. Each sample fell on the same side of the
regression line for the AnyBody model and the
experiment. The same pattern can also be seen at
Figure 6 which show the quotient of the normal
force from the AnyBody model divided by the
normal force from the experiment. It can be seen
that variation of the quotient was smaller than the
variation of each of the experiments.
6
inclination was increased, the backrest carried
more and more weight in both the experiment and
the model. The absolute ratio that was carried by
the backrest was less than 1% in difference from
The as
offset
could ofalso
interpreted
a Two Backrest Bars
Multiplication factor
a Function
The be
Average
Height as
of the
the experiment to the model. Figure 8 show the seat
10
multiplication
factor. Figure 6 shows the quotient
shear force plotted against the backrest angle. The
between the AnyBody-predicted and the measured
graph shows again similar trends for the model and
force 8values of Figure 5. The figure indicates
the experiment however the model overshoots the
strongly that the model over-estimate the
shear forces. The figure clearly shows that the
experimental
values by a factor of 2.
6
trends are consistent for model and experiments,
also in terms of variations from the linear
4
regression.
Fn / N
This indicates that differences in postures have
been interpreted in the same way in the AnyBody
model as it was in the experiment.
Seat120Shear Force as a Function of Backrest Angle
2
0
0.24
100
0.26
0.28
0.3
0.32
0.34
0.36
0.38
0.4
0.42
Avg. Height / m
Fs - AnyBody
Fs - Experimental
LinReg Fs - AnyBody
LinReg Fs - Experimental
Fs / N
80
Figure 6. The quotient of normal forces from the
AnyBody model divided by the normal forces from
the experiment.
60
40
Effect of changing the backrest angle
20
The next result was found by investigating how
much of the model/subject’s weight was carried by
the seat and footrest when changing the backrest
angle and keeping the seat in horizontal. The result
can be seen in Figure 7 and it shows the added
normal forces at the footrest and the seat
1
Fn (seat+footrest) / Backrest Angle
Normalized Fn / N
0.98
0.97
0.96
0.95
0.94
88
90
92
94
96
98
100
90
92
94
96
98
100
102
Backrest-seat relative angle / Degrees
Figure 8. The seat shear force plotted against the
backrest angle.
Effect of changing the seat angle
Fn - AnyBody
Fn - Experimental
LinReg Fn - AnyBody
LinReg Fn - Experimental
0.99
0
88
102
Backrest-seat relative angle / Degrees
Figure 7. The normal force at the seat plus the
footrest plotted against the backrest angle. The
forces have been normalized with respect to the total
weight of the model/subject.
normalized with respect to the weight of the model
and the subject respectively. As the backrest
Next the seat angle was varied while the backrest
inclination was maintained at 10 degrees. Two
output measures were plotted in Figure 9 and
Figure 10. Figure 9 shows the shear force at the
seat plotted against the seat angle. The seat angle is
zero for horizontal and negative as the seat is
leaned back. The shear force increased as expected
when the seat was raised to horizontal. The result
shows the same phenomenon as before with points
falling on the same side of the regression line for
the experimental forces and the model-estimated
forces and the experimental result being lower than
the results from the model.
Figure 10 shows the normal force applied to the
backrest plotted against the seat angle. Here the
trends are not exactly equal, and contrary to
previous results the residuals from the linear
7
regressions were high indicating a nonlinear
relationship between seat angle and backrest force.
will consist of a relatively higher degree of
voluntary applied force bearing less weight.
Most likely it is a consequence of the relatively
high negative value of shear force at the seat that
was found in the experiment. The nonlinearity was
similar in the experimental data and the model
predictions.
Shear force (Fs) as a Function of Seat Angle
Gildorf, P. et.al. (1991) also mounted a forceplate
as a wheelchair seat and measured normal and
shear forces for different backrest angles. They
found average shear force at the seat for a hard
surface at 5˚ incline to be 27 N, which was very
close to what was found experimentally in the
present study, indicating that the test subject was
typical and the prediction by the model were too
high. High predictions by the model could be
caused by the algorithm used to solve AnyBody
models. The algorithm as described in [21] tries if
possible to minimize the maximum muscle activity
by applying a greater force on for example the
backrest.
Fn at Backrest as a Function of Seat Angle
120
100
80
Fs - AnyBody
Fs - Experimental
LinReg Fs - AnyBody
LinReg Fs - Experimental
Fs / N
60
40
20
0
-20
120
-40
-10
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
Seat Angle / degrees
4.
DISCUSSION
The results revealed similar trends in model and
experiment in almost all situations. However the
AnyBody model overestimates the backrest force
and thereby also the seat shear force by a factor of
two. This could be an artefact from the model, or it
could be caused by a non-typical muscle
recruitment of the test subject. Bush, T.R. &
Hubbard, R.P. (2007)[22] found that the thorax and
pelvis together applied a normal force to the
backrest of Fn = 212 N with a standard deviation of
50 N for experiments on 23 men which also were
chosen to fit a 50th percentile man. The 212 N was
measured at a backrest angle of 20˚ from vertical,
which is more than investigated in the present
study. For instance the result presented at Figure 5
with the backrest in vertical position there was a
difference between the experiment and the model
of approximately 30 N. This seems like a nice
result, especially because higher variations would
be expected as the backrest is moved towards
vertical because the normal force at the backrest
100
Fn / N
Figure 9. The seat shear forces plotted against the
seat angle. The backrest was leaned back 10˚
110
90
80
Fn - AnyBody
Fn - Experimental
LinReg Fn - AnyBody
LinReg Fn - Experimental
70
60
-10
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
Seat Angle / degrees
Figure 10. The normal force applied to the backrest
plotted against the seat angle. The backrest was
leaned back 10˚
However the model was intended to give detailed
information on how change in seated posture
affects the reaction forces at the chair. Generally it
models how parameters interact. Validation of
interaction predictions should be validated with
respect to the interaction, i.e. the trend, in order to
get a good quality model. [16]
The friction coefficients chosen for the seat and
footrest were investigated in a sensitivity study.
Two coefficients where varied and the shear force
at the seat estimated by the model was measured.
The result showed that choosing friction
coefficients above µ=0.15 the model was not
sensitive to changes of the friction coefficient,
8
indicating that assuming µ=0.5 would not influence
the result significantly.
Only one subject was included in this study,
therefore the inter individual variation in unknown,
however the intra individual variation showed low
variations between measurements (see table 1).
The normal force applied to the seat and footrest
plotted against the backrest angle showed almost
no differences between the experiment and the
model, neither in the absolute values nor in the
trend, due to the result in this case depends almost
exclusively on the segment masses and not on
muscle recruitment.
Experimentally a few things could have been done
differently. The AnyBody model was driven with
markers placed at bony landmarks, which worked
reasonably well, except maybe the thorax. The
angle between the thorax and pelvis was driven in
the sagittal plane by a marker at the sternum. If the
subject has a different thorax depth, i.e. thickness
from the sternum to the spine, then the model
would lean too much forward. There were no
markers at the back of the subject so this could not
be checked. It was observed visually that the
subject did lean up against the backrest bars which
the model did not. In a future experiment a marker
could be placed at the back of the subject to
improve the thorax posture registration. Another
experimental issue is the range of the different
input parameters. They should have been bigger to
improve the confidence of the trend measurements.
For example the backrest should have been leaned
back to 30˚ instead of only 10˚, which would have
improved the comparison with the results reported
by Bush, T.R. & Hubbard, R.P. (2007)[22].
There was also a modelling issue concerning the
center of mass (CoM) for the model compared to
the experiment. It is hard to estimate the CoM for
any given segment in a human model and it is
consequently unknown how the assumed CoMs of
the model compare with the test subject
anthropometry. The CoM for the upper body was
moved to the position where the model had
minimum muscle activity for a seated position with
a minimum of support by the backrests. This
position could have been checked experimentally,
by seating the subject with no backrest support,
measuring the CoM for the whole body, and
correcting the CoM for the upper body in the
model based on this result.
One output parameter was not investigated in detail
was the ratio of forces at the footrest compared to
the seat. This could have been investigated by
changing the seat depth and the seat height to see
how the footrest/seat ratio would change.
5.
CONCLUSION
The AnyBody model estimates reaction forces at
the chair with the same trends as what can be
measured experimentally but tends to over-estimate
the forces. More experiments are necessary to
clarify why this happens.
This pilot study showed good preliminary results
indicating that the model estimates changing forces
when the seat is adjusted.
6.
ACKNOWLEDGMENTS
This study is a part of the Seated Human Project
partially sponsored by RBM A/S. The support is
gratefully acknowledged. The authors also wish to
thank Wolturnus A/S for their great help
constructimg the custom-built wheelchair for the
experiment.
6.
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9
[3] Gefen, A., 2007, "The Biomechanics of
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