Erik F Jensen1, Joakim Raunsbæk1, Jan N Lund1, Tariq Rahman2, John Rasmussen3, Miguel N Castro3. 1. Department of Health Science and Technology, Aalborg University, Aalborg, Denmark. 2. Department of Biomedical Research, Nemours/Alfred I DuPont Hospital for Children, Wilmington, DE, USA. 3. Department of Materials and Production, Aalborg University, Aalborg, Denmark.
Abstract
INTRODUCTION: People who are born with arthrogryposis multiplex congenita are typically not able to perform activities of daily living (ADL) due to decreased muscle mass, joint contractures and unnatural upper extremity positioning. They are, therefore, potential users of an assistive device capable of aiding in ADL and increasing their independence. A passive orthosis can support the weight of their arm against gravity, allowing them to perform movements with less effort. METHODS: This study presents a prototype design with four degrees-of-freedom that uses musculoskeletal modelling to optimize the stiffness of the springs in the device to partially gravity balance the upper extremity while compensating for the usual internally rotated glenohumeral joint. A single subject-specific musculoskeletal model was developed to simulate the effects of the passive orthosis during 10 static postures during ADL. RESULTS: For a given configuration using a mono- and a bi-articular spring, the simulations showed that spring stiffnesses of 400 Nm-1 and of 1029 Nm-1, respectively, were able to lower the maximal muscle activity estimated by the musculoskeletal model to a level in which the 10 postures can be realized. CONCLUSION: By augmenting residual muscle strength with a partially gravity-balanced passive orthosis, ADLs may be achievable for people with arthrogryposis multiplex congenita.
INTRODUCTION: People who are born with arthrogryposis multiplex congenita are typically not able to perform activities of daily living (ADL) due to decreased muscle mass, joint contractures and unnatural upper extremity positioning. They are, therefore, potential users of an assistive device capable of aiding in ADL and increasing their independence. A passive orthosis can support the weight of their arm against gravity, allowing them to perform movements with less effort. METHODS: This study presents a prototype design with four degrees-of-freedom that uses musculoskeletal modelling to optimize the stiffness of the springs in the device to partially gravity balance the upper extremity while compensating for the usual internally rotated glenohumeral joint. A single subject-specific musculoskeletal model was developed to simulate the effects of the passive orthosis during 10 static postures during ADL. RESULTS: For a given configuration using a mono- and a bi-articular spring, the simulations showed that spring stiffnesses of 400 Nm-1 and of 1029 Nm-1, respectively, were able to lower the maximal muscle activity estimated by the musculoskeletal model to a level in which the 10 postures can be realized. CONCLUSION: By augmenting residual muscle strength with a partially gravity-balanced passive orthosis, ADLs may be achievable for people with arthrogryposis multiplex congenita.
The movement capabilities of the upper extremities are essential for independence.[1] Arthrogryposis multiplex congenita (AMC) is a disorder in which people often
lack these movement capabilities. This disorder is classified as a heterogeneous
group of diseases with more than 300 different conditions, with the main
characteristic involving multiple congenital joint contractures.[2,3] The prevalence of AMC is 1 in
3000 live births.[4] The most common type of AMC is amyoplasia, which is a combination of
decreased muscle mass and joint contractures with some distinct characteristics;
typically the shoulders are adducted and internally rotated, the elbows are extended
and the wrists are flexed and ulnarly deviated.[3-6] However, these anatomical
characteristics might differ between subjects.[5] Decreased muscle mass is usually found in the deltoids, the biceps brachii
and the brachialis muscles.[3] The combination of contractures and muscular weakness makes activities such
as self-feeding, reaching the face and handling objects difficult or impossible.[7] The occurrence of amyoplasia is sporadic, and the genetic cause is still
unknown.[8,9]
The exact aetiology is also unknown, but among a number of factors, foetal akinesia
is a prevalent factor in developing AMC.[5]Treatment of subjects with amyoplasia is performed in different ways, primarily to
improve the quality of life and enable activities of daily living (ADL).[3,9] Physical therapy, stretching and
splinting are used to mobilize the joints and stimulate muscle growth.[6,10] Surgery is another treatment
method primarily targeting the lack of elbow flexion.[4] Concerning passive elbow flexion, surgical procedures have shown excellent
results in regard to increased passive motion and improved independence for feeding.
Due to lack of active elbow flexion, performing ADL still requires compensatory
techniques such as using the assistance of the opposite arm or propping the arm
against a table.[11] The outcome of surgical procedures intended to improve active elbow flexion
are encouraging. However, according to Lahoti and Bell,[12] a progressive increase in flexion deformity and decrease in the arc of
flexion were observed over time. As an alternative to the therapeutic and surgical
methods, there has been moderate research in assistive devices, such as orthoses,
that are able to compensate for the muscular weakness of the upper extremities and
assist the subject in performing ADL.[13] Passive devices are based on the static balancing principle by using
potential elastic energy stored in mechanical components such as zero-free-length springs.[13] These orthoses may be used by people with AMC to aid in ADL. Orthoses allow
for the increased use of the arms, thus aiding in the development of muscle.
Kroksmark et al.[14] emphasize the importance of muscle development over treatment of
contractures, since the muscular strength is more important for motor function. This
may be achieved using a partially gravity-balanced system.[15]There are different commercially available passive orthoses that can balance the arm
in a wide range of configurations. An example of a passive orthosis is the
Wilmington Robotic Exoskeleton (WREX).[7] The WREX is a four degrees-of-freedom (DOF) passive device using
parallelograms to gravity balance the upper limb. Another device is A-gear, relying
on multi-articular springs to balance two serial linkages.[16] The latter approach is based on a recent formulation called the stiffness
matrix approach which is a planar energy-based method.[17] This method was extended from polar coordinates to Cartesian coordinates by
Lustig et al.[18] The A-gear consists of one mono-articular spring spanning the elbow joint and
one bi-articular spring spanning both shoulder and elbow joints.[16] However, a limitation associated with this fully gravity-balanced
configuration is that the springs' attachments on the lower arm are determined by
the length and masses of both upper- and lower arm segments which makes it too bulky
to fit underneath clothing.[19]In the present work, a subject-specific passive orthosis prototype with four DOF was
designed to bring the internally rotated glenohumeral joint into neutral position
while providing assistance through an increased range-of-motion for subjects with
amyoplasia. Similar to the A-gear, the orthosis uses two zero-free-length springs to
counterbalance gravity in different upper extremity configurations, plus an extra
shoulder internal/external rotation assistive spring. In order to improve the
compactness of the orthosis, musculoskeletal modelling was used to simulate a
partially gravity-balanced configuration of the orthotic device taking the
subject-specific muscular weakness into account. Therefore, the characteristics of
an idealized amyoplasia patient were simulated in the model. The muscle recruitment
for sustaining a given set of static postures was later assessed using the model
with and without a designed orthotic device. Each spring stiffness was selected by
minimising the maximum muscle activation (MMACT) required to sustain those postures.
The results will be presented and discussed with the purpose of setting guidelines
for further studies.
Methods
Anthropometric data from one healthy male subject (age: 26, mass: 70 kg, height:
178 cm) were acquired in the current study with the aim of setting the
musculoskeletal modelling background. The subject was initially equipped with 20
reflective skin markers attached to the pelvis, trunk, shoulder and right arm. The
position of the reflective markers was recorded using an eight-camera motion capture
system (Qualisys AS, Gothenburg, Sweden) at a sampling frequency of 100 Hz.
Kinematic data were analysed using the AnyBody Modelling System 6.1 (AMS) (AnyBody
Technology, Aalborg, Denmark), and a static trial was conducted in neutral position
as reference to scale the model to the subject.
Musculoskeletal modelling
In order to simulate the effects of the orthosis on the human body, an upper
extremity musculoskeletal model was created in AMS from the built-in repository
v1.6.3. The model is based on the lumbar spine data from the work of de Zee et al.,[20] while the shoulder, upper and lower arm data belong to the work of the
Delft Shoulder Group.[21-23] The
musculoskeletal model comprises eight DOF: three DOF at the sternoclavicular
joint, three DOF at the glenohumeral joint and two DOF at the elbow joint. The
static trial was used to geometrically scale the model to the subject by the
method of Andersen et al.[24] as presented in Figure
1. This is a local optimization-based method which minimizes the
least-square differences between marker trajectories and the markers defined on
the musculoskeletal model. In total, the musculoskeletal model included 140
simple muscle model elements. Their nominal strength was scaled according to a
Length-Mass-Fat Scaling law,[25] which is a general scaling method capable of estimating the nominal
strength from the body segments' mass and length, with the inclusion of a fat
percentage based on the body height–weight ratio. In AMS, the internal forces
and moments from muscles and joints are found by formulating a complete set of
Newton-Euler equations for dynamic equilibrium, relating all segments' inertial
properties within the model.[26] The inverse dynamics analysis solves those equations from prior results
obtained in the kinematic analysis in which the state of the system obtained for
each time instant of the recorded motion. The number of muscle elements is far
greater than the number of DOFs in the model, rendering the equilibrium
equations under-determined – this is known as the redundancy problem of the
muscle recruitment.[27] The physiological mechanism of muscle activation is controlled by the
central nervous system but is still not well understood. Therefore, the muscle
recruitment in musculoskeletal modelling is typically based on an optimality
condition, where the central nervous system minimizes the loads across the
different muscles. The min/max muscle recruitment criterion developed by
Rasmussen et al.[27] was used in this study, and it distributes the muscle forces in such a
way that the overall MMACT is minimized. The min/max criterion is suitable for
this study since, in maximal effort tasks, it delays fatigue by ensuring maximal
muscle synergism.
Figure 1.
(a) The kinematic data collected during a static trial from the
reflective markers set constant trajectories was used to
geometrically scale the musculoskeletal model. (b) The captured
markers (blue coloured) were approximated by each respective marker
(red coloured). The method of Andersen et al.[24] helps optimising the green-arrowed markers in the model which
do not belong to a specific bony landmark.
(a) The kinematic data collected during a static trial from the
reflective markers set constant trajectories was used to
geometrically scale the musculoskeletal model. (b) The captured
markers (blue coloured) were approximated by each respective marker
(red coloured). The method of Andersen et al.[24] helps optimising the green-arrowed markers in the model which
do not belong to a specific bony landmark.In order to obtain realistic posture inputs for the musculoskeletal model, motion
capture data for 10 different ADL were obtained. These ADL motions were selected
from those suggested by Rosen et al.[28] and a representative posture of each was selected. An unconstrained
segment usually requires three reflective markers attached to describe its
motion, thus resulting in nine DOF. This introduces over-determinacy because a
segment only has six DOF. Furthermore, the joint constraints imposed by the
human body further increase that gap leading to an over-determinacy problem.
This over-determinacy introduced by the marker coordinates was solved using the
method of Andersen et al.[29] The 10 different postures are illustrated in Figure 2, and these were simulated by the
musculoskeletal model. The majority of these tasks usually involve the hand
reaching a point in space, grasping an object and then controlling and orienting
the object until the task is completed.[30] Examples of important ADL include feeding and personal hygiene, which
includes touching the face and head.[31] Being able to perform these tasks can provide more independence to the
user as well as improve their quality of life.
Figure 2.
The 10 different postures used for the inverse dynamic analyses.
The 10 different postures used for the inverse dynamic analyses.The output measure in the current study is based on the MMACT, which determines
whether the muscle system is able to produce the joint moments required to
balance the system for each static posture. The muscle activity is the ratio
between required produced force and each muscle's nominal strength. If the MMACT
is greater than one for any given muscle, there is insufficient strength to
maintain the posture. However, in the case of a simulated disabled subject
unable to use a given DOF, all muscles actuating that DOF are removed from the
model. In order to enable the inverse dynamic solver to establish equilibrium,
an additional artificial ‘diagnostic’ muscle is added to balance the specific
DOF. This ‘diagnostic’ muscle is a torque provider which will be recruited
whenever the required DOF torque is beyond what is provided by the orthosis in
order to attain the required posture. For the specific case of amyoplasia, both
elbow and glenohumeral flexion are compromised as reported by Kowalczyk and Feluś.[3] Therefore:All muscles with a positive contribution to elbow flexion and the
anterior deltoid were disabled and substituted by a very weak elbow
flexion torque provider.The joint and muscle contractures were not included in the model.The inverse dynamics analyses were performed for static postures only.
Orthosis modelling
A prototype of a passive orthosis, using zero-free-length springs, was designed
to assist in the performance of ADL. In light of what was previously mentioned,
the orthosis must be able to support and follow the movements of the shoulder
and elbow. The movements will be aided by mechanical springs capable of
counterbalancing gravity. In addition, an extra spring will aid the external
rotation of the user's glenohumeral joint, thus bringing the humerus into a more
neutral position. A secondary goal is that the motion enabled by the orthosis
can aid in the promotion of muscle development.[6,32] The orthosis CAD model can
be seen in Figure 3.
Figure 3.
(a) Full orthosis DOFs: 1. Shoulder elevation/depression; 2. Shoulder
abduction/adduction; 3. Shoulder flexion/extension; 4. Shoulder
internal/external rotation; 5. Elbow flexion/external. (b) Full
orthosis springs configuration: mono-articular spring
(S1); bi-articular spring (S2);
internal/external rotation assistive spring (S3).
(a) Full orthosis DOFs: 1. Shoulder elevation/depression; 2. Shoulder
abduction/adduction; 3. Shoulder flexion/extension; 4. Shoulder
internal/external rotation; 5. Elbow flexion/external. (b) Full
orthosis springs configuration: mono-articular spring
(S1); bi-articular spring (S2);
internal/external rotation assistive spring (S3).The system combining the human arm and the orthosis is shown schematically in
Figure 4. The inner
lines represent the human arm, while the outer lines represent the orthosis. The
orthosis is in parallel with the upper extremity supporting its anatomical
glenohumeral joint, represented as a spherical joint with three DOF
(θa1, θa2, θa3), and elbow joint which is
represented with one DOF. The orthosis itself is composed of five revolute
joints: θo1 allows for elevation/depression of the shoulder; the
three revolute joints θo2, θo3 and θo4
represent the three DOFs of the shoulder, abduction/adduction, flexion/extension
and internal/external rotation, respectively; and the connection between the
upper arm shell and the forearm shell is created by a revolute joint
θo5, which represents elbow flexion/extension. A gimbal lock
occurs in this shoulder mechanism when the shoulder abducts more than 90°
flexion. However, a study by Buckley et al.[33] has found that the required shoulder abduction for ADL is usually less
than 90°. Dunning and Herder[13] have also suggested that a possible design could be to neglect the full
vertical range-of-motion of the shoulder, focusing only on the support of the
most essential daily tasks. The orthosis was created to function within this
recommended range. The whole system is supported by: a bi-articular spring,
S1, originating above the glenohumeral joint and inserting on
forearm link spanning both glenohumeral and elbow joints; a mono-articular
spring, S2, located along the humerus and posterior to the elbow
assisting the extension. On the humeral-lateral aspect of the orthosis, a rail
is attached, whereas the slider is attached to the elbow joint. As the shoulder
internally and externally rotates, the slider follows accordingly. Considering
that one of the most common patterns of deformity in the upper extremity due to
amyoplasia is the internal rotation of the shoulder,[9] the purpose of this mechanism is to aid the alignment of the shoulder
into a neutral position. The assistive spring, S3, is attached using
two parallel points located on the lateral aspect of the humerus and the slider.
On the humerus, anteriorly and posteriorly located between the attachments,
there are two pulleys. As the user internally or externally rotates the humerus,
the pulleys act on the spring, increasing the force and tension as the slider
moves further, bringing and aligning the humerus into a more neutral position.[9]
Figure 4.
(a) Schematic of the musculoskeletal model (inner lines) and orthosis
model (outer lines) system. The joints connecting both models are
illustrated by the purple symbols. All DOF and mechanical joint
angles are represented by black arrows. (b) The three springs are
presented by dashed lines. (c) The orthosis CAD model connected to
the musculoskeletal model as described.
(a) Schematic of the musculoskeletal model (inner lines) and orthosis
model (outer lines) system. The joints connecting both models are
illustrated by the purple symbols. All DOF and mechanical joint
angles are represented by black arrows. (b) The three springs are
presented by dashed lines. (c) The orthosis CAD model connected to
the musculoskeletal model as described.To determine whether the orthosis is capable of fulfilling its intended function,
the interaction between the orthosis and the human body has to be examined. In
this study, the essential aspect of the musculoskeletal modelling is the
simulation of how the human body is affected by the external forces produced by
the orthosis and gravity. The CAD model of the orthosis along with the mass
properties of the individual parts of the orthosis were imported into AMS. To
establish the human–orthosis interaction system, the orthosis was attached to
the musculoskeletal model through three predefined reference nodes located on
the thorax, the humerus and the ulna. The attachments between the human arm and
the orthosis were defined and modelled as mechanical joints. The upper arm
attachment was modelled as a spherical joint, θc1, θc2,
θc3 and the forearm attachment as a trans-spherical joint, with
three rotations θc5, θc6, θc7 plus a
translational DOF θc4 as illustrated by the symbols drawn in the
middle of each segment of the musculoskeletal model in Figure 4.
Simulation specifications
In order to investigate a suitable and favourable spring configuration that
yields the lowest average MMACT for the 10 postures, 10 corresponding numerical
studies were conducted. Three different springs (Figure 4) were available for load
balancing. The ranges of spring stiffnesses and initial locations for the
parameter study were determined by the method of Lustig et al.[18] For the bi-articular spring, the applied stiffness range 0 to
700 Nm−1, and for the mono-articular spring, it was 0 to
1200 Nm−1. The ranges of the two springs were covered in 15 steps
in the parameter study, resulting in 225 different combinations of spring
configurations for each of the 10 postures. Because Lustig et al.'s method is
two-dimensional, the stiffness of the internal/external rotation spring was
merely chosen from available zero-free-length springs (Synthetic Polyisoprene,
Jaeco Orthopedic, Arkansas, USA) to 84 Nm−1 and remained
unchanged.The ideal forearm attachment points for the mono- and bi-articular spring were
calculated to 10.25 cm anterior to the elbow joint and 7.7 cm posterior to the
elbow joint, respectively. However, in the interest of compactness, the spring
attachments site for the bi-articular spring was relocated to 5 cm anteriorly to
the elbow and the mono-articular spring was attached 7.2 cm posteriorly to
elbow. This creates an imbalance, but the goal was to investigate whether the
arm could still be sufficiently gravity balanced to allow the subject to perform
ADL with the residual muscle function (typical patients have some remaining
glenohumeral and elbow flexor strength).A schematic of the mechanism and respective spring configuration used in the
present study can be seen in Figure 5, while the values used and calculated can be found in Table 1. For every
step of each parameter study, an inverse dynamics analysis was performed and an
MMACT value was obtained. To assess the stiffness for both mono- and
bi-articular springs that would yield the lowest MMACT in the biomechanical
model, the average MMACT across all 10 postures was calculated and plotted for
each of the 225 spring configurations. In addition, the five different global
strength factors (0.2, 0.4, 0.6, 0.8 and 1.0) were pre-multiplied with the
nominal strength of each muscle element in the biomechanical model in order to
test whether the strength would influence the results.
Figure 5.
Schematic of the mechanism with the representation of stiffness
matrix inputs for the Cartesian coordinates formulation of Lustig et al.[18]
Table 1.
The calculated spring stiffnesses and spring placements using the
method of Lustig et al.,[18] the six values above the line are calculated, while the
values below it are set to constant values.
Parameters
Values
ax1 (m)
0.0000
bx1 (m)
0.1026
by1 (m)
0.0009
bx2 (m)
−0.077
by2 (m)
−0.0006
k1 (Nm−1)
382.15
k2 (Nm−1)
756.00
ay1 (m)
0.0700
ax2 (m)
0.0920
ay2 (m)
0.0000
m2 (kg)
2.2940
m3 (kg)
1.6820
L2 (m)
0.2800
sx2 (m)
0.1275
sy2 (m)
0.0000
sx3 (m)
0.1662
sy3 (m)
−0.0011
Schematic of the mechanism with the representation of stiffness
matrix inputs for the Cartesian coordinates formulation of Lustig et al.[18]The calculated spring stiffnesses and spring placements using the
method of Lustig et al.,[18] the six values above the line are calculated, while the
values below it are set to constant values.
Results
The typical surface profile of the average MMACT, as can be seen in Figure 6, was characterized by
a valley towards the minimum value, separating two distinct domains: a very steep
domain characterized by the over-activation of the elbow flexor ‘diagnostic’ torque
provider and a second domain characterizing the recruitment of the elbow extensor
muscles. Both domains are direct responses to the dominance of either the
mono-articular spring over the bi-articular spring and vice versa, respectively,
always accounting with the strength of the muscle elements in the model. Moreover,
the strength of the model did not influence the result of stiffness for the optimal
springs’ stiffness configuration. The stiffness configuration yielding the lowest
MMACT was composed of mono-articular spring stiffness of 1029 Nm−1 and a
bi-articular spring stiffness of 400 Nm−1.
Figure 6.
Graph showing the average MMACT for all 10 postures with different spring
configurations. Layers are representing different muscle strength
configurations of the muscles. The lowest layer corresponds to a global
strength factor of 1 – no change – while the increasing surfaces
represent consecutive strength decrements of 0.2 units, thus: 0.8, 0.6,
0.4 and 0.2.
MMACT: minimising the maximum muscle activation.
Graph showing the average MMACT for all 10 postures with different spring
configurations. Layers are representing different muscle strength
configurations of the muscles. The lowest layer corresponds to a global
strength factor of 1 – no change – while the increasing surfaces
represent consecutive strength decrements of 0.2 units, thus: 0.8, 0.6,
0.4 and 0.2.MMACT: minimising the maximum muscle activation.The MMACT was then simulated for the 10 posture cases with and without the orthosis
for the previously obtained spring configuration yielding in the lowest average
MMACT. The results regarding these 10 parameter studies are shown in detail in Table 2. The table shows
that the MMACT was greater than 1 in 7 of the 10 postures, when the model was not
wearing the orthosis, which means that model would not be able to attain the
posture. While wearing the orthosis the model could attain all postures.
Table 2.
The maximal muscle activation values for each of the 10 different
postures, with and without the optimal orthosis. When the MMACT is
greater than 1 for any given muscle, there is insufficient strength to
sustain the posture.
Posture
No orthosis (MMACT)
Orthosis (MMACT)
1
26.81
0.07
2
0.10
0.08
3
0.14
0.09
4
17.15
0.07
5
2.85
0.08
6
5.53
0.21
7
1.09
0.06
8
0.10
0.08
9
10.76
0.09
10
21.21
0.06
MMACT: minimising the maximum muscle activation.
The maximal muscle activation values for each of the 10 different
postures, with and without the optimal orthosis. When the MMACT is
greater than 1 for any given muscle, there is insufficient strength to
sustain the posture.MMACT: minimising the maximum muscle activation.
Discussion
In the present study, a musculoskeletal model simulating amyoplasia of a hypothesized
disabled subject with and without the orthosis was used. The spring configuration
found by the use of a parameter study showed that on average a mono-articular spring
stiffness of 1029 Nm−1 and a bi-articular spring stiffness of
400 Nm−1 yielded the lowest average MMACT for the 10 postures. The
orthosis of the current study with the abovementioned stiffness configuration was
able to lower the MMACT for all 10 postures. However, postures 2, 3 and 8 did not
cause any muscle over-activation even without wearing the orthosis. This might
result from the fact that inverse dynamics analyses were performed on static
postures instead of dynamic motion. The results support the idea that a partially
gravity balanced device might still be used for arm assistance of disabled users. In
comparison to the stiffness matrix approach suggested by Lustig et al.[18] which, according to Dunning and Herder,[19] is too bulky to fit underneath clothing, these results suggest the potential
for a more compact device. This not only shows a step forward towards compactness
but also shows the opportunity for creating devices that could exploit some of the
residual muscle function to compensate for the kinetic imbalance, thus promoting
muscle growth and rehabilitation of these users.In order to imitate amyoplasia, several assumptions were made regarding the
musculoskeletal model. Zhou et al.[34] have shown that a specialized model can be used to design different types of
exoskeletons based on different neuromuscular conditions. The specific muscles
affected may differ between different subjects due to amyoplasia being heterogeneous
and very individual.[5] The model can potentially enable the adjustment of the strength of specific
muscle elements, making the model subject-specific, thus optimizing the stiffness of
the springs to the user. The musculoskeletal model does not account for the
contractures typically seen in amyoplasia, which may have produced different
results. These contractures could have been modelled as passive stiffness in the
joints. The muscles in the model were modelled with constant nominal strength,
whereas the Hill's muscle model is a more realistic representation in which
force–length and force–velocity relationships can be included, thus making room for
more muscle parameter adjustments.[35,36] With the consideration of
these factors, further developments should validate the effectiveness of the
orthosis, for example, by the use of the method of Castro et al.,[37] enabling the simulation of the full reachable workspace and investigating
whether it increases by wearing the orthosis model.
Conclusion
The current study found that musculoskeletal modelling may be a useful tool to
calculate spring stiffness for partially gravity-balanced devices. This method may
enable identification of spring stiffness for subject-specific orthotic devices that
would allow for the performance of ADL with the potential to act as a rehabilitation
device. Further studies should implement subject-specific strength measurements from
a user with amyoplasia, such that it reliably represents the subject, and use
dynamic motions to test the effect of the orthotic device of its user. Furthermore,
the parameter study can be extended, such that spring locations can also be
optimized to find the optimal relationship between spring location and spring
stiffness for the best performing device. Ideally, in the future, individual muscles
may be targeted, thus opening a window for the development of orthoses, thereby
enhancing treatment of amyoplasia.
Authors: Tariq Rahman; Whitney Sample; Shanmuga Jayakumar; Marilyn Marnie King; Jin Yong Wee; Rahamim Seliktar; Michael Alexander; Mena Scavina; Alisa Clark Journal: J Rehabil Res Dev Date: 2006 Aug-Sep
Authors: Tariq Rahman; Whitney Sample; Rahamim Seliktar; Mena T Scavina; Alisa L Clark; Kacy Moran; Michael A Alexander Journal: IEEE Trans Neural Syst Rehabil Eng Date: 2007-06 Impact factor: 3.802