ergonomic considerations for anthropomorphic wrist exoskeletons: a simulation study on the effects...
Post on 30-Dec-2015
11 Views
Preview:
DESCRIPTION
TRANSCRIPT
Ergonomic considerations for anthropomorphic
wrist exoskeletons: a simulation study on
the effects of joint misalignment
Mohammad Esmaeili, Kumudu Gamage, Eugene Tan, and Domenico Campolo∗
School of Mechanical and Aerospace Engineering, Nanyang Technological University, 639798 Singapore
Abstract—This work focuses on anthropomorphic exoskeletonsfor the human wrist. We consider a 2 dof model for the humanwrist with non intersecting joints and a similar model for theexoskeleton. We assume a viscoelastic attachment between thehuman hand and the handle of the exoskeleton which on one sideallows the different kinematics of the exoskeleton to follow thehuman wrist and, on the other side, induces reaction forces at alljoints, in particular causing discomfort. We quantify discomfortas the amount of potential energy stored in the deformation ofthe viscoelastic attachment.
For a specific exoskeleton implementation, based on kinematicsimulations, we report the kinematic mismatch (i.e. differencesbetween the human joints and the corresponding exoskeletonjoints) as well as the reaction forces arising when the humanjoints assume postures throughout their physiological range ofmotion. Considering a typical distribution of joint offset forhumans (derived from literature) and the asymmetry in thediscomfort function (derived from our simulations) we addressthe ‘one-size-fits-all’ problem and propose an optimal joint offsetfor the exoskeleton, based on the minimization of the aggregateloss function.
I. INTRODUCTION
Human-machine interaction is a central topic in the field
of robotic exoskeletons (exos) and more recently ergonomic
factors are being systematically included since the early phases
of design [1], [2]. Exos can be divided into two main cat-
egories: anthropomorphic and non-anthropomorphic [3]. In
this paper we present ergonomic considerations, based on
kinematic simulations, for anthropomorphic exos meant to act
in concert with the human wrist.
Discomfort in wearing an exo is due to interaction forces
between human and exo arising at those locations where the
exoskeleton is attached to the human limb. Such forces result
from ‘kinematic discrepancies’ [4], due for example to over-
simplified models of human kinematics and/or misalignments
between human and exo joints [5].
Most of the modern approaches propose the use of extra
degrees of freedom (dof) for compensating joint misalign-
ments. Such extra dof are passive, while only the joints which
correspond to the human ones are meant to be actuated. While
introducing extra dof clearly helps reducing or eliminating
kinematic discrepancy (for example, a 6dof structure can
*Corresponding author d.campolo@ntu.edu.sg. This work is sup-ported by the Academic Research Fund (AcRF) Tier1 (RG 40/09), Ministryof Education, Singapore, and the New Initiative Fund 2010 (NTU).
surely adapt to a human wrist, at least within a certain range),
it should be noticed that, when the extra dof are present
but locked during normal operations, a kinematic mismatch
might still arise, i.e. joint angles at corresponding exo and
human joints no longer coincide. Although some recent studies
focused on reaching-movements for robot-assisted rehabilita-
tion for the wrist districts [6], [7], [8], [9], [10], the effect
of kinematic mismatch on robot control strategies, especially
in relation to neurorehabilitation, received relatively less at-
tention. Most control strategies, in fact, assume that driving
(imposing motion or torque) a robotic joint is equivalent to
driving the corresponding human joint.
In this paper, we do consider extra dof only for the
purpose of wearing the exoskeleton, e.g. different subjects
might require different positioning of the handle, but we
will consider that all the extra dof as locked during normal
operation. Therefore, from a kinematic perspective, the wrist
exoskeleton will comprise only 2dof mobility at joints which
are, in principle, aligned with human ones.
We shall consider a physiologically accurate 2dof model of
the human wrist, which comprises an offset between the two
human joints. Such an offset is known to vary from subject to
subject, with a distribution experimentally derived by [11]. In
our study, we assume that the misalignment between human
and exo occurs at the both proximal and distal joints along
the offset between them.
The human hand and the exo handle represent the end-
points1 of two dof structures, for any non-zero misalignment,
the position and orientation of the hand would be obviously
incompatible with the position/orientation of the handle. In
reality, the hand is not a perfectly rigid body, due for example
to the skin compliance and to the possible adjustment in
the grasping. For this reason we hypothesize that contact
between hand and handle is non-rigid and occurs through
some springs. In this study we assume linear springs and
this is clearly a simplification, nevertheless interesting features
such as asymmetry in the reaction forces can be captured, as
discussed next.
As for the structure of this paper, the model of human wrist
and exoskeleton is described in Section II, the prototype of
1The other endpoint is where the exo is attached to the forearm, we assumethis attachment much more rigid than the hand-handle one, see for example[12, Chapter 5].
2011 IEEE/RSJ International Conference onIntelligent Robots and SystemsSeptember 25-30, 2011. San Francisco, CA, USA
978-1-61284-456-5/11/$26.00 ©2011 IEEE 4905
our exoskeleton is presented as well. Then, we present the
simulation and data analysis and show how misalignments
lead to kinematic mismatch between exo joints and human
wrist counterparts. As the results of our study, the reaction
forces in wrist joint and the deformation energy in the hand-
handle attachment points is presented. Subsequently, as ‘one-
size-fits-all’ concept, we compute the optimal joint offset for
exoskeleton to have the least discomfort. Finally, in section
IV, the results are discussed.
a) b)
Fig. 1. Exoskeleton with hand model. a) Configuration of the exoskeletonalongside the wrist. b) SimMechanics model.
II. METHODS
A. Modeling the human wrist
The human wrist is a complex joint with 2 degrees of
freedom (dof) responsible for radial-ulnar deviation (RUD,
distal) and flexion-extension (FE, proximal). Despite small
changes in the instantaneous center of rotation for each joint
during rotations, a widely accepted approximation is to assume
ideal revolute joints for both degrees of freedom. The simplest
models assume a universal joint [13]. In reality, the FE and
RUD axes are almost orthogonal and non-intersecting [14] and
the joint offset of between the RUD and FE axes is known to
vary among subjects. Leonard et al. [11] investigated, with
noninvasive measurements, the distribution of the offset for a
population of 108 subjects and reported a 6.8mm mean inter-
axes offset with a distribution as shown2 in Fig. 2.
−20−16−12−8 −4 0 4 8 12 16 20 24 280
0.5
1
Joint axes offset [mm]
Fre
qu
en
cy
Fig. 2. Normalized frequency distribution of wrist joint rotation axes offset,based on [11].
Based on the above considerations, we developed a kine-
matic model of the human wrist in the SimMechanics (Math-
Works Inc.) environment. As shown schematically in Fig. 3,
2Note: the values were digitized from the original work [11].
Fig. 3. Functional diagram of the wrist and exoskeleton. Through a chain oflinks and joints human wrist is connected to the exoskeleton. Joint offset isconsidered for the both wrist (δ) and exoskeleton (δexo). Misalignment (m)is applied on the exoskeleton joints throughout the simulations.
the model consists of series of three rigid bodies3, the most
proximal being the forearm (fixed) and the most distal be-
ing the hand, connected to one another via revolute joints.
We considered two orthogonal joints ωwristFE (proximal) and
ωwristRUD (distal) and with an offset between the two axes (‘joint
offset’) along the longitudinal axis of the forearm (Y-axis).
Each joint has an associated joint angle: θFE and θRUD
for the FE and RUD axes, respectively. For the joint angles,
we assumed an average range of motion (RoM) as [-50 35]
degrees for θRUD and [-65 70] degrees for θFE .
B. The modeling of the exoskeleton
For the exoskeleton, we considered an anthropomorphic
structure, i.e. a 2dof mechanism with revolute joint axes ωexoRUD
and ωexoFE with a similar proximal-distal order and aligned with
the anatomical counterparts. As for the alignment, as we shall
see next, a variable misalignment will be purposely introduced
to analyze its effects.
The proximal end of the exoskeleton is meant to be attached
to the forearm, and therefore fixed. The distal end of the
exoskeleton is attached to the hand through the handle. While
for the forearm we can resort to optimal attachments methods
which minimize skin motion effects, e.g. see the splinting
proposed in [15], the hand-handle attachment is more prone
to relative motions and, to the authors’ knowledge, much less
analyzed in literature. For this reason, we assumed a perfect
attachment between human forearm and the proximal side
of the exoskeleton while we assumed a non-rigid attachment
between human hand and handle. This non-rigid attachment
is implemented via a set of four non-collinear ideal springs
which are meant to allow some degree of relative motion
between human hand and handle during grasping. This is
clearly a rough approximation and its required experimental
validation by the authors is still on-going at the time of writing.
Nevertheless, we refer to similar approaches performed by
Schiele et al. on [1] although not specifically for the hand-
handle attachment. We heuristically set the stiffness constant
3The middle body is simply used to introduce an offset between the twojoints.
4906
to the four springs equal to 2000 N/m. The use of four
non-collinear springs results in a translational and rotational
stiffness throughout the movements which are considered in
potential energy (see III-C).
Besides the FE and RUD joints which are supposed to mir-
ror the human counterparts, the exoskeleton is also endowed
with a number of ‘passive’ joints. Such passive joints are
required to adapt the exoskeleton itself to the different size
of end users.
Remark: the passive joints are meant to be locked while
the exoskeleton is in use. The model used in our simulations,
described next, takes into account the full structure of the
exoskeleton. This is important for future studies, when the
inertial properties of the exoskeleton will also be considered.
Fig. 4. Prototype of the exoskeleton. Besides, the FE and RUD joints of theexoskeleton which are supposed to mirror the human counterparts, the extrapassive joints are considered to align the exoskeleton with different size ofend users.
C. Simulation and data analysis
Although in this study we are interested in the ergonomics
of the exoskeleton from a kinematic perspective, in our sim-
ulations we implemented the full structure of the exoskeleton
as shown in Fig. 4, comprising the inertial properties of
each element. Given the elastic and the inertial properties
present in the model, transient behaviors would inevitably
arise after each step of the inputs. For this reason, we also
added linear dampers in series to each spring, to dampen
out any mechanical resonance due to the elastic properties
of the springs and the inertial properties of the exoskeleton.
Heuristically, we set the linear damping coefficients to 1.0
N/(ms−1) as this generated overdamped behaviors, quickly
leading to steady-state conditions.
In order to analyze the steady-state conditions for different
human wrist postures, FE and RUD joints in the human wrist
model are actuated according to a sequence of discrete values
corresponding to a 11 × 9 matrix of values covering the RoM
mentioned in II-A.
SimMechanics is a continuous time simulator, so discon-
tinuous, step-like transitions between two discrete values of a
joint angle would elicit long-lasting transient behaviors, while
we are only interested in steady-state conditions. In order to
generate smooth transitions between discrete values of each
joint angle, we used the jtraj function, distributed with
the MATLAB Robotics Toolbox [16], which implements a 7th
order polynomial interpolation.
As seen from Fig. 5, the combined effect of smooth tran-
sitions between discrete values of the human joint angle and
the overdamped response of the system ensures short transient
behaviors. The steady-state conditions of the angles for both
human and exoskeleton joints can be reliably sampled at fixed
time intervals (circles in Fig. 5).
9.7 9.8 9.9 10 10.1 10.2 10.3
−5
0
5
time [s]
θR
UD [deg]
Exo Human Sampling Sampling
Fig. 5. Steady-state sampling represented in time domain. Blue dash-lineis the active movement of wrist followed by exoskeleton (red solid line)passively. Circles are the samples chosen when system is in steady-statecondition.
By sampling at these very fixed time intervals, we were able
to extract the steady-state values for the following variables
(for both the human wrist and the exoskeleton):
• kinematics: angular position, angular velocity and angular
accelerations for FE and RUD joints;
• reaction forces (F r): amplitude4 of generated forces due
to misalignments for FE and RUD joints, computed as
Fr =√
F 2x + F 2
y + F 2z
• discomfort function: for each misalignment, we compute
the mean value over the workspace of the elastic energy
of the springs between hand and handle5 (see Fig. 3);
4Single force components could be analyzed as well, but we found noqualitative difference.
5Although rather arbitrary, we noticed no qualitative difference whenchoosing the mean value of reaction forces or kinematic mismatch betweenhuman and exo joint angles.
4907
Therefore, for each posture of the human wrist, we extracted
the corresponding values for the physical variables described
above.
We repeated the simulation for different possible misalign-
ments between the RUD/FE joint of the exoskeleton and the
RUD/FE joint of the human wrist. In particular, based on the
work of Leonard et al. [11] in Fig. 2, a misalignment distribu-
tion6 was considered. The choice of range of misalignments
was dictated by the aggregate loss calculations explained later.
NOTE: just for programming convenience, the human joint
offset was held constant while the misalignment was generated
by varying the exoskeleton joint offset.
III. RESULTS
A. Kinematic mismatch
We simulated a so-called active mode operation, i.e. de-
sired angles were imposed for the human joints while the
exo passively followed. As expected, except for the case of
perfect alignment, there was a kinematic mismatch between
the exo FE/RUD angles and human counterpart (since the
joint misalignment was for the FE (proximal) joint, the angular
mismatch was obviously found between the human and exo
FE and RUD angles too). Fig. 6 shows a representative
case, for a +12mm joint misalignment. The mismatch grew
approximately linearly with the angle. For the representative
case of +12mm misalignment, there is a 20% relative error,
as shown in Fig. 6.
−50 0 50
−20
−10
0
10
20
θFE
[deg]
θR
UD [
de
g]
Human Exo
Fig. 6. Range of motion of exoskeleton (solid line-crosses) is compared withwrist (dots-circles) for a representative +12mm misalignment on ωexo
FE.
B. Reaction forces at human wrist
Fig. 7 shows the reaction forces at the FE joint of the
human wrist (FrwristFE ) against the range of motion of FE
and RUD joints. These forces are monitored in the presence
of +12mm misalignment between the ωFE of wrist and
exoskeleton. In covering the whole RoMFE , the maximum
amounts of reaction forces occur in the maximum range of
the wrist flexor for the whole RUD joint angles. No reaction
6These misalignments are along the longitudinal axis of the forearm, i.e.in the Y-axis as in Fig. 3.
force is seen throughout the RoMRUD when θFE = 0. For
each FE joint angle the amount of FrFE is almost constant
across RoMRUD .
Note: Since, stiffness of the springs in the attachment points
as well as damping ratio are heuristically selected, we took into
account the normalized values for all forces.
−500
50
−20
0
200
0.5
1
θFE
[deg]θRUD
[deg]
Norm
aliz
ed r
eaction f
orc
eFig. 7. Normalized reaction force on FE joint of wrist over the range ofmotion of FE and RUD for +12mm misalignment on ωexo
FE.
C. Non-rigid attachment
The resulting deformation energy of the four non-collinear
springs, explained in II-B, during movement of the wrist could
be calculated through
U t =4
∑
i=1
1
2ki l
2
i (1)
Where, k is the stiffness and l is the length of each spring
shown in Fig. 3.
−500
50
−20
0
200
0.5
1
θFE
[deg]θRUD
[deg]
No
rma
lize
d d
efo
rma
tio
n e
ne
rgy
Fig. 8. Normalized deformation energy at attachment points of end-effectorfor +12mm misalignment on ωexo
FE.
Fig. 8, illustrates the resulting deformation energy over wrist
RUD and FE angles. It can be seen that, deformation energy
significantly changes across flexion-extension rotations while
it seems less sensitive to radial-ulnar deviations.
4908
Moreover, we calculated the mean values of the deformation
energy for each amount of misalignment and considered the
normalized amount of this deformation energy during move-
ment of wrist as the Normalized discomfort which is shown
in Fig. 9.
−60 −40 −20 0 20 40 600
0.5
1
Misalignment [mm]
No
rma
lize
d d
isco
mfo
rt
Fig. 9. Normalized discomfort over the different amount of misalignments.
D. One-size-fits-all
Since the RUD–FE offset for the exoskeleton cannot be in
principle aligned by simple visual procedures, in this section
we try to estimate which optimal offset, for the exo, would
best fit an entire population, not just a single subject. For this
we shall use the distribution of the joint offsets derived by
Leonard et al. [11] and correlate it with the discomfort caused
by different misalignments, as in Fig. 9.
To this end we shall make use of the concept of ‘aggregate
loss’ [17] which is widely used in the fields of Human
Factors and Ergonomics as well as in Economics. Simply
put: if we have to design a one-size T-shirt meant to fit
an entire population, knowing the anthropomorphic data of
a population and knowing that each individual will claim a
refund proportional to the amount of discomfort (a positive
function of size mismatch), what is the optimal size that will
minimize the total refund (aggregate loss)?
One might be tempted to design a T-shirt that fits the
average size (from the population distribution) any asymmetry
in the population distribution or in the discomfort function
(e.g. better a T-shirt too large rather than too small) might
induce better choices.
In our case, the distribution PDF (δ) of joint offsets (δ)
for the population sampled by Leonard et al. [11], reported
in Fig. 2, does not present remarkable asymmetries, with the
average offset being δ = 6.8mm. On the other hand, the
discomfort U(m), function of misalignment (m), is highly
asymmetric due to mounting the exo in the interior side of
the wrist, as shown in Fig. 9. An exoskeleton with offset δexo
worn by a person whose anatomical offset is δ, would cause a
discomfort U(δexo−δ). Therefore, the aggregate loss L(δexo),for a specific choice of exoskeleton offset, is
L(δexo) :=
∫
PDF (δ)U(δexo − δ) dδ
Fig. 10 shows the aggregate loss numerically estimated from
the data available from Leonard et al. [11] and the simulated
discomfort function.
−20−16−12 −8 −4 0 4 8 12 16 20 24 280
10
20
30
Joint axes offset [mm]
To
tal d
isco
mfo
rt
Fig. 10. Density of total discomfort over the range of wrist axes offset.The mean of total potential energy for a set of misalignment is taken intoconsideration in calculating total discomfort.
The optimal offset for the exoskeleton is numerically found
to be
δexoopt := argminL(δexo) = 4 mm
IV. CONCLUSION
We evaluated the transparency of an exoskeleton in presence
of misalignments between human and mechanical joints. In
particular, we evaluated the response of the exoskeleton in
terms of kinematic mismatch and reaction forces in wrist joint
by simulating imposed movements at the human joints (within
a physiological range of motion). Although the exoskeleton
in Fig. 4 comprises various extra (prismatic) joints, to allow
different users to wear the exoskeleton, during operation all
these extra prismatic joints are meant to be locked. Therefore,
the exoskeleton is a 2dof system. Any misalignment would
make it kinematically incompatible (kinematic discrepancy)
with the human 2dof wrist unless some compliance is allowed.
The distal part of the exo is attached to the hand through a
handle while the proximal part is meant to be attached to the
forearm. We focused on the hand-handle attachment since, is
more prone to relative motion and is less addressed in litera-
ture, to the authors’ knowledge. To do so, we considered a non-
rigid attachment between hand and handle by implementing a
set of four non-collinear springs.
Our simulations quantified the amount of kinematic mis-
match between the human joint angles and the exo counter-
parts caused by joint misalignment.
Such a kinematic mismatch should be taken into account
especially when the exoskeleton is being driven, imposing
movement to the human joints. Typically, it is assumed perfect
match between human and exo joint angles while our simula-
tions show that large errors (e.g. 20% relative error in Fig. 6)
might arise. This suggests that the human joint angles should
be measured separately from the exo joint angles.
Although the exo joints are not actuated in our study,
reaction forces still arise due to kinematic mismatch, as
highlighted by our simulations. As mentioned in [4], kinematic
discrepancy is one of the causes for reaction forces. Since
our exoskeleton is located on the volar side of the wrist, it
causes asymmetric kinematic mismatch between exoskeleton
and wrist for flexion rotations in presence of misalignments.
4909
Therefore, larger amounts of reaction forces occur during wrist
extension, rather than flexion (see Fig. 7). These reaction
forces do not perform work on the human joint but cause
discomfort, or worse, pain.
When a misalignment between human and exo joints is
present, the end-effector does not closely follow the hand
making the non-collinear springs to stretch or compress,
causing deformation energy. Due to the structure of the ex-
oskeleton and its position (volar part of the wrist), deformation
energy has an asymmetric profile with regard to rest position
of FE (θFE = 0) with larger deformation energies during
flexion. To have a natural movement without perturbation, it
is needed to have the least resistance against the motion in
any voluntarily movement over the range of motion of human
joint. The occurrence of the reaction forces on the joint would
cause a perturbation on the movement because of the low
impedance/stiffness of the limb.
Despite the oversimplifications, this work highlighted that
misalignments would result in kinematic discrepancies and
generation of interaction forces in pHRI. Kinematic mismatch
would then make an exoskeleton ‘non-transparent’, causing
movement perturbation. Since, the discomfort is asymmetric,
choosing an offset for the exoskeleton based on the average
offset for the human joints, might not be optimal from a
‘one-size-fits-all’ perspective. Based on the aggregate loss
minimization concept, we numerically found that a 4mm offset
for the exo joints, instead of a 6.8 mm average (as from the
experimental distribution of human offsets), would actually
determine the optimal one-size-fits-all.
REFERENCES
[1] A. Schiele, “An explicit model to predict and interpret constraint forcecreation in pHRI with exoskeletons,” IEEE/ICRA, 2008, pp. 1324–1330.
[2] N. Jarrasse and G. Morel, “On the kinematic design of exoskeletonsand their fixations with a human member,” in Proceedings of Robotics:
Science and Systems, Zaragoza, Spain, June 2010.
[3] F. Sergi, D. Accoto, N. L. Tagliamonte, G. Carpino, and E. Guglielmelli,“A systematic graph-based method for the kinematic synthesis of non-anthropomorphic wearable robots for the lower limbs,” Frontiers of
Mechanical Engineering in China, 2010.
[4] N. Jarrasse, M. Tagliabue, J. Robertson, A. Maiza, V. Crocher, A. Roby-Brami, and G. Morel, “A methodology to quantify alterations in humanupper limb movement during co-manipulation with an exoskeleton,”Neural Systems and Rehabilitation Engineering, IEEE Transactions on,vol. 18, no. 4, pp. 389–397, 2010.
[5] A. Schiele and F. van der Helm, “Kinematic design to improve er-gonomics in human machine interaction,” IEEE Transactions on Neural
Sys and Rehab Eng, vol. 14, no. 4, pp. 456–469, 2006.
[6] D. Campolo, D. Formica, E. Guglielmelli, and F. Keller, “Kinematicanalysis of the human wrist during pointing tasks,” Experimental brain
research, vol. 201, no. 3, pp. 561–573, 2010.
[7] N. Tagliamonte, M. Scorcia, D. Formica, F. Taffoni, D. Campolo, andE. Guglielmelli, “Force control of a robot for wrist rehabilitation: Copingwith human motor strategies during pointing tasks,” RSJ Advanced
Robotics Journal, vol. 25, pp. 537–562, 2011.
[8] D. Campolo, D. Accoto, D. Formica, and E. Guglielmelli, “Intrinsicconstraints of neural origin: Assessment and application to rehabilitationrobotics,” Robotics, IEEE Trans on, vol. 25, no. 3, pp. 492–501, 2009.
[9] F. Sergi, D. Accoto, D. Campolo, and E. Guglielmelli, “Forearmorientation guidance with a vibrotactile feedback bracelet: On thedirectionality of tactile motor communication,” in Biomedical Robotics
and Biomechatronics, 2008. 2nd IEEE RAS & EMBS International
Conference on, pp. 433–438.
[10] D. Campolo, F. Widjaja, M. Esmaeili, and E. Burdet, “Pointing with thewrist: a postural model for donders law,” Experimental Brain Research,vol. 212, no. 3, pp. 417–427, Jun. 2011.
[11] L. Leonard, D. Sirkett, G. Mullineux, G. Giddins, and A. Miles,“Development of an in-vivo method of wrist joint motion analysis,”Clinical Biomechanics, vol. 20, no. 2, pp. 166–171, 2005.
[12] J. Pons, Wearable robots: biomechatronic exoskeletons. Wiley OnlineLibrary, 2008.
[13] D. Williams, H. Krebs, and N. Hogan, “A robot for wrist rehabilitation,”in IEEE/EMBS 2001, vol. 2, 2001, pp. 1336–1339 vol.2.
[14] J. Andrews and Y. Youm, “A biomechanical investigation of wristkinematics,” Journal of Biomechanics, vol. 12, no. 1, pp. 83–93, 1979.
[15] E. Rocon, A. Ruiz, J. Pons, J. Belda-Lois, and J. Sanchez-Lacuesta,“Rehabilitation robotics: a wearable Exo-Skeleton for tremor assessmentand suppression,” in IEEE/ICRA 2005, pp. 2271–2276.
[16] P. Corke, “A robotics toolbox for MATLAB,” Robotics & Automation
Magazine, IEEE, vol. 3, no. 1, pp. 24–32, 1996.[17] C. Hsu, “Developing accurate industrial standards to facilitate production
in apparel manufacturing based on anthropometric data,” Human Factors
and Ergonomics in Manufacturing, vol. 19, no. 3, pp. 199–211, 2009.
4910
top related