|
Items in cart [0] |
Questions? Call 888-624-8373 |
PAPERBACK Free Resources |
||||||||||||||||
|
||||||||||||||||
|
||||||||||||||||
| ||||||||||||||||||||||||||||||
|
||||||||||||||||||||||||||||||
| Copyright © 2009. National Academy of Sciences. All rights reserved. Terms of Use and Privacy Statement |
Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter.
Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 19
3
Biomechanical Models
Interest in the biomechanical properties of the human body
has evolved along with mathematical sophistication. The early
works of Leonardo da Vinci (O'Malley and Saunders, 1952), Galileo
Galilei (1638), and Giovani Alfonso Borelli (circa 1679) demon-
strate man's curiosity ~d desire to describe the human in quan-
titative terms. Even though hundreds of years have passed since
these early attempts, biomechanical modeling of the human mus-
culoskeletal system remains one of the most challenging tasks
known to man.
This chapter evaluates biomechanical modeling knowledge and
its significance to ergonomics. Prior to such a review, however,
the concept of modeling as used here should be discussed first. A
mode} can be defined as any set of equations that describe phys-
ical events or phenomena. Sinclair and Drury (1980) described a
mode} as a paradigm view of science. They proposed two defini-
tions of models. First, they defined a mode! as "the result of using
theoretical understanding to present a particular aspect of the real
world. This definition represents a normative model, which de-
scribes the idealized behavior of the system. Second, they defined
another type of descriptive mode] that used Statistical techniques
to relate theoretical variables present in a collection of data. This
type of model typically employs regression analysis to describe the
dynamic behavior of the human body.
In the context of this review of biomechanical models, only
19
OCR for page 20
20
models according to Sinclair and Drury's first definition will be
considered.
Consideration must be given to the objective of a biomechan-
ical mode! used for ergonomic purposes. A biomechanical mode]
should facilitate the basic understanding of the system. Morris
(1967) noted that modeling should be a process of enrichment and
enhancement. He pointed out that one should begin with a mode!
that is distinct from reality and, in an evolutionary manner, move
toward a more elaborate mode! that reflects the complexity of the
actual situation. Little (1970) stated that the objective of the
mode} should be to provide intuition. It is apparent that these
two objectives are complementary. Through a process of under-
standing the components of a system, the mode! is expanded and
a greater understanding of component interaction is gained.
To achieve these objectives, a mode! should display several
qualities. The model should be robust. It should display the
essence of the system under a variety of circumstances. A biome-
chanical mode! should also represent reality and have clinical rel-
evance or workplace applications.
The significance of these objectives and requirements applied
to ergonomics means that biomechanical models should provide
insight into the interaction of people and their environment. Ide-
ally, an ergonomic mode} should predict both long- and short-term
results of human work, and the effects on people, particularly if a
risk exists for both traumatic and cumulative injuries.
The discussion on biomechanical models is limited to those
models that may be useful to ergonomists. Hence, impact, physim
logical, and psychophysical models are not included in this review,
nor are all existing models of the musculoskeletal system. Instead,
examples are presented that concern bones, joints, body segments,
and the whole body.
HISTORY OF BIOMECEANICAL MODELS
As noted in Chapter 2, Anthropometric Models, the early
models of the 1960s assumed that the body is a series of rigid
links. These models were limited in the number of links, usually
one, two, or three. Most of the models were two-dimensional,
based on kinematic information, with some dynamic data. The
objective was to look at the forces, torques, and moments around
OCR for page 21
21
the various articulations and then to track the links to determine
what type of loading or motion occurs.
Some of the models were then extended, but none predicted
any of the internal loadings on the body. Most of the early models
worked in some way with the external loadings, based primarily
on kinematic types of information and characteristics of torque
and force generated by the link motions. Some models, like that of
SIote-Stone (1963), were used in predicting power and some, like
that of Ayoub et al. (1974), were used in predicting position during
work. These models provider! the basic context of understanding
in the programs.
Many of the later models are based on the work of Chaffin
(1969), who joined seven or eight different links of the body. Ex-
tending the previous principles, he calculated torques and forces
around the joint, and then tracked the whole body in a kinetic
chain. Most of the later models are two-dimensional static models
that represent, to a limited extent, forces and moments acting at
each particular articulation to generate internal loading informa-
tion. More recent versions of this model are built on the same
basic logic but use dynamic data and three dimensions.
Ayoub and El-Bassoussi (1976) used optimization to predict a
lifting model, and in the early 1980s, Schultz and Andersson (1981)
and Schultz et al. (1982) developed a different type of model that
no longer considered the body as a set of rigid links. This was
a three-dimensional model that represented active analysis of the
stresses imposed on the body under working conditions. This two-
part analysis can be used to analyze the net reaction which must
be resisted by the internal forces of the body. Several methods
have been used for this type of analysis. One is to assume that the
antagonist muscles are silent (which may or may not be a correct
assumption, depending on the circumstances), and another is to
use optimization, particularly linear programming with upper and
lower bounds.
Another class of new models is that described by Hatze (1976,
1977~. This is a complex model that accurately predicts forces in
the leg when a person takes a step with a weight tied onto the leg.
It represents advanced techniques that may be useful for future
ergonomic modeling.
OCR for page 22
22
REVIEW OF BIOMECHANICAL MODELS
One of the more basic evaluations that occur in biomechani-
cal modeling is the analysis of moments and forces that act on a
body segment in a work environment. Chaffin (1982) performed
an analysis of such forces for single- and two-body segments un-
der static planar conditions. In these cases Newtonian mechanics
were applied to the segments and the system was evaluated in a
state of static equilibrium. When multiple body segments were
involved, each body segment was evaluated as a separate link in
a kinetic chain system. A two-link model of the arm was devel-
oped by Pearson et al. (1961, 1963~. It computed the forces and
torques present at the elbow and shoulder caused by the motion
of arm, forearm, and hand in the sagittal plane. This analysis
required data obtained from stroboscopic photography to caTcu-
late the instantaneous position, velocity, and acceleration of the
arm, forearm, and hand system. Together with the known values
of mass ant] length of the body segments, these data were used
to compute the forces and torque present caused by the motion.
Extensions of this mode! were developed by Plagenhoef (1966),
who modeled whole-body motion based on kinematics.
Predictive equations for hand motion in workspace design have
been developed by Kattan and NadIer (1969), and SIote and Stone
(1963) modeled acceleration patterns of the upper extremity. Ay-
oub et al. (1974) also developed a two-segment, three-dimensional
motion mode! of the upper extremity. This mode! was unique,
however, in that it used optimization (dynamic programming) for
a solution to perform a movement. It predicted hand position in
space during certain movements. However, Ayoub and coworkers
(1974) stressed the need for more detailed evaluation of mode!
assumptions. This work demonstrated the feasibility of using oh
timization techniques to mode} the external loading factors of a
biomechanical system.
Several biomechanical models that evaluate stress caused by
external loads during lifting have been presented in the litera-
ture. Models by Chaffin (1967) and Chaffin and Baker (1970) are
static, sagittal plane extensions of the major body segments and
were expanded to predict the compressive forces sustained by the
lumbar spine. They demonstrated how predicted moments gener-
ated about the body articulations could be compared with human
strength characteristics, and suggested that this method be used
OCR for page 23
23
to evaluate the physical strength capability and requirements of
manual materials-handling activities. This model assumed that
lifting occurs slowly and smoothly, so that the effects of accel-
eration are negligible. This approach has been adopted by the
National Institute for Occupational Safety and Health (NIOSH,
1981) for evaluation of the workplace.
A three-dimensional static strength evaluation analysis was
described by Garg and Chaffin (1975~. Chaffin and Andersson
(1984) also discussed how multiple-link static models could be used
to evaluate reactive moments of the body in both coplanar and
nonplanar analyses, how modeling techniques assess the moments
experienced by joints during motion, single- and multiple-segment
dynamic modeling techniques, and how biodyna~nic analysis tech-
niques could be used to assess pushing tasks. Aunts et al. (1980)
developed a method to estimate moments about the elbow during
maximum flexion. These techniques employed high-speed photo-
graphic techniques to predict angular velocities and acceleration.
Inertial forces and resistance moments that must be produced by
the muscles could then be calculated. Ereivalds et al. (1984) used
this technique to study dynamic lifting.
The models that have been described take into account the
stresses and loads caused by an external load or motion imposed
on the body. Some of these models also evaluate internal forces.
These assumed that the body is composed of several rigid links
which are joined by articulations. The analyses usually consist of
evaluations of the motions and loads imposed on these structures
via traditional Newtonian mechanics. Recently, some optim~za-
tion techniques have been used and represent a promising area of
endeavor. Chaffin (1969) developed a seven-link, two-dimensional
static model to calculate joint forces and moments during material-
handling activities. The model also computed the spinal compres-
sion force during lifting. This model was later expanded to include
three-dimensional static strength prediction (Chaffin et al., 1977;
Garg and Chaffin, 1975~. Freivalds et al. (1984) also expanded
this model to evaluate the sagittal plane kinematic activity. All
of these models consider the effects of both external and internal
loading when considering the compressive forces on the spine.
El-Bassoussi (1974) and Ayoub and El-Bassoussi (1976) de-
veloped a model which predicts stresses on the muscuToskeletal
system by infrequent tasks in the sagittal plane. The mode! used
predicted movement dynamics based on the findings of Slate and
OCR for page 24
24
Stone (1963~. This mode! is dynamic and considers subject move-
ment and the forces that are generated because of these mover
meets. Ayoub et al. (1980) compared the virtues of these lifting
models. They pointed out that the limitation of most lifting mod-
els for ergonomic purposes is that they only estimate stresses
within the body when work is performed in the sagittal plane and
few of them consider motion. Gruver et al. (1979) developed a
five-link, two-dimensional mode! of the human body to simulate
manual lifting tasks.
These models just described are limited by the fact that most
are two-dimensional planar models. These models help us to un-
derstand the loading of the body in sagittally symmetric exertions.
Many of the more challenging ergonomic concerns, however, in-
volve loading of the body in three dimensions. For many tasks the
body is loaded in a torsional fashion. Assessment techniques are
required to evaluate these situations.
Another limitation of existing models concerns the ability to
assess the consequences of motion. Many of the analysis techniques
are static and do not consider the effects of velocity or acceleration
of the body part or load when assessing the biomechanical cost
to the system. Some models have been reported in the literature
that consider motion; however, the motion assessment is usually
limited to the sagittal plane, and often, the effects of load weight
are not considered.
Basic research is required which addresses the question of
whether a kinetic link system portrayal of the biomechanical sync
tem is appropriate. Some assumptions regarding the shape and
length of link elements are necessary for simplification purposes.
Freivalds et al. (1984) pointed out that the spine could be better
represented by some semiflexible arrangement. Thus, a rigid beam
link analogy may not be the best method of modeling the human
system. This is also evident from the previous discussion regarding
bone modeling.
The models described in this section describe techniques for
assessing the reactive moments and forces at each articulation
that must be exerted by the muscles. These reactive moments
and forces are necessary to overcome the forces imposed on the
biomechanical system by external loads and body weights. These
models have been used successfully to match worker capabilities to
the demand of the task. They provide insight into worker selection
rationale.
OCR for page 25
25
Ergonomic models should be capable of assessing the trau-
matic ejects as well as the cumulative effects of the work. To
achieve this objective, ergonorn~c models should be able to evalu-
ate the loading of the articulation and skeletal structures caused
by the external and internal loadings. Internal loading refers to the
forces supplied by the muscles and ligaments that react to the ex-
ternal loads; thus, both external and internal forces load the body.
The significance of internal forces to the loading of the body has
been discussed by Cailliet (1968) and Tichauer (1978~. Knowledge
of the effects of internal and external forces is necessary to predict
the instantaneous loading of the body articulations and skeletal
structures. Models that include internal forces are usually much
more difficult to use since there are often more unknown muscle
forces than there are independent equations available to solve the
problem. Thus, a unique solution is not possible, and the problem
becomes statically indeterminate.
Models of Bones
Work on the biomechanics of bone and load-bearing capability
of bone dates back over three centuries to Galileo Galilei (1638)
and has progressed to modern stress analysis techniques (Burstein
et al., 1970; Minns et al., 1977; Piotrowski and Wilcox, 1971;
Toridis, 1969~. Others (Brown et al., 1980; Hayes et al., 1978;
Huiskes et al., 1981; Olofsson, 1976; Piziali et al., 1976; Rohimann
et al., 1982; Rybicki et al., 1972; Scholten et al., 1978; Valliap-
pan et al., 1977, 1980) used finite-element models of the femur
which assume that bone is an isotropic and homogeneous mate-
rial, even though it is nonhomogeneous and is described as being
transversely isotropic. The femoral model described by Vallia~
pan et al. (1977, 1980) used a finit~element analysis to compare
the stress distribution in the femur for both a prosthesis mode!
and a normal femur. The stresses were computed both with and
without the anisotropic assumption of transverse isotropy, and
two loading conditions were used, walking and one-legged stance.
The stress distribution was found to change significantly when the
anisotropic assumption was used for cortical bone; however, no val-
idation of results was mentioned. Others (Goe! et al., 1978; Hayes
et al., 1982; Oonishi et al., 1983; Snyder et al., 1983; Williams
and Lewis, 1982) developed finite-element models for other bones,
such as the pelvis, patelIa, and trabecular bone. A summary of
OCR for page 26
26
the merits of many of the finite-element models used in orthopedic
biomechanics was prepared by Huiskes and Chao (1983) and elan
orates on the details of the models. It does not include a discussion
of a finite-element mode! of a lumbar vertebra.
Hakim and King (1979) subjected a bilaterally symmetric
finite-element model of a lumbar vertebra to static and dynamic
loads. The cortex and plates and spongy bone of the vertebral
body were modeled with thin plate and shell elements and three-
dimensional isoparametric elements. The pedicle, lamina, and
articular facets were represented with brick elements, and the
facets were modeled to provide articulation such as that in a true
facet joint. Plate elements were used to represent the processes.
Material properties data from the literature were used, and input
load distribution was taken from experimental data (Hakim and
King, 1976~. Validation efforts showed a favorable comparison
between computed and measured strains. Balasubramanian et al.
(1979) extended this mode} to simulate a unilateral laminectomy
and bilateral asymmetric loading.
Vibration data have been used to determine in viva elastic
properties of long bones, another area of bone modeling. Jurist
and Kianian (1973), Orne (1974), Orne and Mandke (1975), Orne
and Young (1976), and Viano et al. (1976) have all studied the
elastic property of bone in this manner.
Models of Single Joints
In viva internal forces and moments at a joint are both difficult
to measure and calculate, largely because of the involvement of
many muscles and ligaments, which results in more unknowns than
there are equations. Electromyogram (EMG) data, minimum total
muscular force and/or moment, and minimum total mechanical or
metabolic energy are used to reduce the number of unknowns.
Equations in dynarn~c models are usually nonlinear differential
equations. They are reduced to algebraic equations by electing to
solve the "inverse dynamic problems in which kinematic data are
supplied as input to eliminate the derivatives.
Models of the Hip and Enee Joints
The knee has been modeled in various ways by Bresler and
Franke! (1950~; Kettelkamp and Chao (1972), Engin and Korde
OCR for page 27
27
(1974), Crowninshield et al. (1976), Harrington (1976), Andriacchi
et al. (1977), Hight et al. (1979), Chand et al. (1976), Wismans
(1980), Wismans et al. (1980), and Minns (1981~.
Morrison (1968, 1969) computed muscle and ligament forces
for a normal gait, while eliminating forces in muscles with quies-
cent EMG data and eliminating ligament forces that become slack
during the specific phases of gait. Experimental force plate data
were used along with photographic identification of the hip, knee,
ankle, and foot to provide joint displacement and rotation data.
EMG data of principal muscle groups were acquired from bipolar
surface electrodes.
Six equations of motion were used to determine the net re-
action force and moment at the knee. When solving for bone
contact force components and the muscle and ligament forces,
the problem became indeterminate. Use of EMG data eliminated
the antagonistic muscle forces and ligament functions and allowed
calculations of bone contact or joint force. The results were com-
parable for repeated tests of the same subject but varied from
subject to subject.
Another method of reducing indeterminacy is to compute the
forces in the ligaments across the knee joint as a function of knee
flexion angle. A ligament mode! developed by Wismans et al.
(1980) assigned stiffness values to the ligaments. This mode! also
considered three-dimensional kinematics of the knee joint and ar-
ticular surface geometry, which established the conditions of con-
tact on medial and lateral surfaces. With this information, 16
unknowns were calculated, including relative joint location, con-
tact points and forces medially and laterally, relative abduction
and rotation, and the magnitude of the joint constraint moment.
The results were principally kinematic and did not provide kinetic
data, which would have been helpful. In a more complete work
by Wismans (1980), kinetic data were also not provided. Rheo-
logical models of the knee by Moffatt et al. (1976) arid Pope et al.
(1976) were based on oscillatory tests that described the knee as
a Maxwell fluid or a Kelvin solid.
Hip joint models were developed in much the same way as
those for the knee (Crowninshield et al., 1978; Noel and Svensson,
1977; Williams and Svensson, 1968~. Paul (1967) assumed that
the hip joint transmitted a contact force and that no more than
two muscles were active at any instant of gait. Kinematic and
force plate data were required by this model.
OCR for page 28
28
For the ankle, t~vo-~unensional models were developed by
Brewster et al. (1974), Stauffer et al. (1977), and Wynarsky and
Greenwald (1983~; and a three-dimensional model was developed
by Procter and Paul (1982~.
Models of Joints of the Upper Extremity
With assumptions of a hinge joint with three major flexors,
the elbow becomes simple to simulate. Based on the work of
MacConaiD (1967), Yea (1976) used linear progrmnming to com-
pute the total forces generated in the muscles. Because the mode!
results contradicted experimental data that show that ad three
muscles are active during flexion, Yea claimed that the Minimum
principle" was not valid. Cro~vninshield (1978) defined maximum
allowable tensile stress in each of three muscles, and his objective
function was minimum total tensile stress. The mode} correlated
wed with experimental data for both isometric and isokinetic con-
tractions. This approach was extended by An et al. (1983) to
compute joint contact forces.
Modeling efforts for the shoulder include the work of DeLuca
and Forrest (1973), who used isometric abduction.
Models of :Intervertebral Joints
Schultz and Andersson (1981) developed a practical threw
dimensional, statically indeterminate mode} which calculated loads
placed on a lumbar vertebra during physical activity. This mode}
functioned in two parts, similar to the knee model, and consid-
ered the action of both the spinal musculature and the abdominal
muscles. The net reaction across a lumbar vertebra, derived from
equilibrium considerations, formed the determinate portion of the
problem. Linear programming was used to determine the resultant
spinal loads and muscle forces while minimizing spinal compress
sign. Large spinal compression forces were predicted for minor
activities and were validated with myoelectric activity indicating
muscular tension. This mode} was later modified by Schultz et al.
(1982), who changed the objective function to specify minimum
~ ,, ~
intensity or stress.
Other researchers developed models of ~ single intervertebral
joint (Belytschko et al., 1974; Kulak et al., 1976; Lin et al., 1978~.
They were able to determine the responses of the intervertebral
OCR for page 29
29
disc. The cIann that such a mode} could be used to predict mate-
rial properties of the joint using optimization was a new concept.
These disc models were loaded axisymmetrically, which is a phys-
iologically incorrect assumption.
Redundancy and validation continue to be the major problems
encountered in the modeling of joints. The use of optimization to
solve the redundancy problems is now acceptable; however, the
choice of an objective function remains an unresolved problem.
This difficulty ~ linked to the inability to validate the predic-
tions of the models. Reliable methods and transducers have not
been developed at this time to achieve the goal. Pedotti et al.
(1978) proposed the use of nonlinear optimization schemes that
had closer correlations with EMG data than did linear schemes,
and Crowninshield and Brand (1981) proposed a mode! that re-
quired a minnnum muscle stress and that correlated with EMG
activity. These approaches, however, did not reduce the difficulty
in the choice of an objective function. An et al. (1983) opined that
linear optimization tenth inequality constraints was superior to a
nonlinear scheme.
Models of Multiple Body Segments and the Whole Body
This class of models can be divided functionally into models of
five groups: (1) the fingers and thumb; (2) the lower extremities,
including gait; (3) the spinal column; (4) the thorax; and (5) the
whole body, excluding gait.
Modem of Fingers and the ThnTr~h
Many researchers have developed modem of the fingers and
thumb, from kinematic models (Landsmeer, 1961) to two-dimen-
sional models (Hirsch et al., 1974; Smith et al., 1964) to three-
dimensional thumb models (Cooney and Chao, 1977; Taft and
Berme, 1980~. Other models were developed by Chao et al. (1976),
Spoor and Landsmeer (1976), Berme et al. (1977), Chao and An
(1978a,b), and An et al. (1974~.
There are many problems encountered in the modeling of a
finger, as discussed in a series of papers by Chao et al. (1976),
Chao and An (1978a,b), and An et al. (1974~. These models were
thre~dimensional and were indeterminate because of the large
OCR for page 32
32
histories to ensure that the input was realistic. Gait was then gen-
erated by solving the differential equations of motion by using an
existing three-dimensional human link model which was developed
originally by Calspan Corporation for the simulation of occupant
kinematics in an automobile crash. It is also known as the artic-
ulated total body (ATB) model, a more complete description of
which can be found in the section by that title in Chapter 4. The
ATE model was modified to accept joint moments as input.
Models of the Spinal Column
An early three-dimensional static mode! of the spine proposed
by Schultz and Galante (1970) generated complex equations that
were not solved. A geometric mode! resulted from the use of fixed-
length elements. This was followed by work by Panjabi (1973), who
developed a general formulation for a three-dimensional discrete
parameter mode! of the spine that could simulate responses to
static and dynamic loading. No specific mode} was proposed.
Belytschko et al. (1973), however, developed a three-dimensional
structural mode! of the entire spinal column with responses to
three loading cases. This mode! simulated vertebrae, ligaments,
and soft tissue and provided resistance against axial, torsional,
bending, and shear loads. The results were validated against
experimental data. Panjabi (1978) has since proposed a model
of a functional spinal unit which could simulate coupled motion.
The disc and soft tissue were represented by a deformable element
such as a viscoelastic body, but because of the lack of material
properties, no model of either a spinal segment or the spinal
column was proposed. Koogle et al. (1979), attempted a three-
dimensional finite-element mode! of the lumbar spine based on
the mesh developed by Balasubramanian et al. (1979), with no
conclusive results. Preliminary results, however, from a finite-
element model of a functional spinal unit formulated by Yang and
King (1984) indicate that it is able to accurately predict intradisc
pressures.
Models of the Thorax
A three-dimensional, bilaterally symmetric, elastostatic, and
finite-element moclel of the human thorax, developed by Roberts
and Chen (1977), was able to reasonably predict rib displacement
OCR for page 33
33
under loading conditions. The ribs were simulated by beam ele-
ments, and geometric and physical rib properties were included.
Sundaram and Feng (1977) developer} both a full thoracic
ant] a skeletal finite-element mode} of the thorax. The former
models simulated the soft tissues and organs of the rib cage, the
thoracolumbar spine, the sacrum, the coccyx, the ribs, and the
sternum. The results of stresses and displacements from 11 static
loading conditions compared favorably with experimental data.
Models of the Whole Body
While several investigators have proposed whole-body mod-
els of human motion not involving gait, many were inspired by
the simulation of movements in space. Kane and Scher (1970)
and Passerello and Huston (1971) formulated models of people in
space and simulated yaw, pitch, and roll maneuvers. Huston and
Passerello (1971) went further to simulate lifting, swimming, and
kicking with one leg.
A lumped-parameter mode! of a seated human (Muskian and
Nash, 1974) simulated the head and torso, which were subjected
to sinusoidal excitation at the seat level. Heart and diaphragm ac-
tivity was also simulated; and responses of the head, back, torso,
and other masses as a function of frequency was given for ~30
Hertz (Hz). Muskian and Nash (1976) proposed a simpler three-
mass mode! which simulated dual load paths from the head to
the pelvis, the spinal column, and the abdominal viscera. Non-
linear frequency-dependent damping was used to simulate actual
responses.
DISCUSSION
King and Marras prepared an extensive table of biomechan-
ical models for this study (Table 3-1) that presents an extensive
overview and summary of the specific variables and parameters
of existing models. They listed the mode} type, input and out-
put variables, mode! characteristics, and the assumptions made
in mode! development. This table is a unique contribution to the
literature and should prove valuable to those who do research on
biomechanical models.
The ultimate goal of biomechanical models should be to create
OCR for page 34
34
~ is
. .`
~ I;
> SS, ~ . , a.
a.. . {a Ha.
_ ~ ~ ~ ,~3 ~ ~ :~:: ISLE 6~ ~~ ~~ 353
~!~
_~: ~
~_
::~? We:: .~=
_
~ ~~:~; ~
1
-
~ _ _
_
= =
= =
= ~
~ W ~ _
~ ~ ~ =
= ~ ~ ~
= _ ~ W
=
~ ~ ~ = =
-
OCR for page 35
35
_ . * -~.~ ,~.~.,.~ ~~.~.~.~ ~ ,~.~ _
~ ~~ _#'.~—2,'~'~'—.~ ::- ,~ Led ~
(by, ~ ~::~:~c~~:: cry: V- ~ ~^, - ~
~ ~ S: . :
S S . ~ .
. it. ~ it
.: . ~ .. if, ~ .... x. me,
~ ~.~,.~..~,^ ~ ~ I,
,..~.. . 4,,,,~ , ~ ~~ . Aim.
~ ~ - . ~ - : ~ ~A, ~
:: ~ Hi
· : ~ ~ i. SS.
,A, Cal, ~.~ .e~ ~~
OCR for page 36
36
l
1
l
1
I Z
1 _
I ~
I ._
1 (A
1 ~
OCR for page 37
37
LE6FND FOR TABLL OF BIOHECHANICAL HODElS
ABO ABDUCTION OR ABDOMINAL
ANISOTROPIC THE MATERIAL DOES NOT HAVE THE SAHE RFSPONSE
ro lOADS fROH DIFFERENT DIRECTIONS
ANNUlUS TNE FIBROUS OUTER RIN6 OF AN INTERVERTEBRAl DIS!
ANrAGON ANTAGONISTIC
AUTO 6EN AUTO-6ENERATION
AVAIL AVAlLABlE
AX AXIAL
AXISYH AXIAL SYHHEIRY IS ASSUMED
BEAH THEORY SIMPLIFIED THEORY OF ElASTICITY APPLIED ro ONE-
DIHENSlONAl PROBLEMS, SUCH AS BEAMS
BILAT BILATERAl
CALC CALCUlATE OR CAlCUlATED
CART CARTIlAGE
CLOSED SOlUTION SOLUTIOH ro A SET ~F DIFFERENTIAL EQUATIONS
c`R,rEe our ANAlYTICALLY IN [ERHS OF A
HATHEHATICAL EXPRESSION
COHB COMBINED OR COMBINATION
COMB / PE RH COHB I NAT ION/ PERMUTATION
COHP COHPRESS1ON OR CO8PRESSIYE
COND CONDITION
CONf OR CONfI6 CONfI6URATION
CONST H OF I THE HASS HOHENT OF INERTIA OF BODY SE6HENTS IS
ASSU8ED ro REMAIN CONSTANT DURIN6 LOCOHOllON
CONTACT HODEl A TECHNIQUE IN ElASTICITY TO COMPUTE CONTACT
STRESSES BETIEEN r~o BODIES rN CONTACT
CORT CORTICAL
D DYNAMIC
DAHP DAHPIN6
DEFl DEFlECTION
DIFF EQS DIFFERENTIAL EOUAllONS
DOF DE6REES OF FREEDOM
DYN EQUIL PRINClPlES OF DYNAMIC EQUILBRIUH dERE
USED ro FORMULATE HODEl
ElASTIC PROPERTIES THE PROPERTIES OF A HAlERIAL ASSOCIATED VIrH rrs
ELASTIC RESPONSE, SUCH AS MODULUS OF ELASTICITY
EH6 ELECTROHYOGRAPHY - THE TECHN[QUE OF HONIlORIN6
ElECTRICAL ACTIVITIES OF MUSCLES
EQUIL EQUILBRIUH
EXT EXTREMITY OR EXTENSION
fEH OR FE FrNITE ElEHENT METHODS OR FINITE ElEHENT
FLEX FLEXION
FUNC SP UNIT FUNCTIONAL SPINAL UNl
INDET INDETERMINATE
lNDIV INDIVIDUAL
INIT INITIAL
INV DYN PROB INYERSE DYNAMIC PROBLEM
6RD REACT 6ROUND REACTION
M-A-I MODEL OF A HUMAN BODY 1N ~HICH THE HEAD, ARHS AND
CONSIDERED AS A SIN6LE HASS
TORSO
OCR for page 38
38
IHPED IMPEDANCE
INCOHP INCOMPRESSIBLE
[NEXT. JTS THE JOINTS BET9EEN BODY SEGMENTS ARE ASSUMED ro
BE INEXTENSIBlE. BODY SE6HENTS CAN ONlY ROTATE
HrrH REsPEcr ro EACH OTHER
Jr JO[NT
KElYIN MODEL A VTSCOElASTIC HODEl ~HICH HAS A HORE SOlID-LIKE
BEHAVIOR
~ IN ~ INEHAT lCS
LAT lATERAl
LIG lI6AHENT OR lIGAHENTOUS
LIN LINEAR
LINEAR ELASTIC THE MODEL ASSUMES rHE BIOL06ICAL HATERIAl ro
BEHAVE IN A LINEARLY ELASTIC MANNER
LINEAR PR06 SOLN SOLUTION ro A SET OF lINEAR AL6EBRAIC EQUATION'
LINEARlY ORTHOTROPIC
LOC
ION
LUH
HAX
HAXlEll MODEL
HCP
HECH
HIN
HOD
HOH
HUSC
NON-LIN
OBJ FCN
PARAH
PHYSIOL X-SECT
PlANE STRAIN
PROB
PRON
PROPS
PROX
REDUNDANT MODEL
RESONANT FREQUENCY
RESP
RH£0l
RIGID BODY
NHICH ARE REDUNDANT, USIN6 THE lINEAR PR06RA8HIN6
METHOD
A HATERIAl ~HICH HAS A lINEAR RESPONSE ro srREs~
BUT HAS ~ ro 12 MATERIAL CONSTANTS
LOCATION
lOdER
lUHBAR
HAXIHUH
A VISCOElASTIC MODEL dHICH HAS A hORE flUID-LI`E
BEHAYIOR
HETACARPAl
HECHANICAl
HEDIAl
HINIHUH
HODEl
HOHENT
MUSCLE OR MUSCULAR
NON-LINEAR
OBJECTIVE FUNCTION USED IN OPTIHI2ATION TECHNIQUES
PARAMETER
PHYSIOL06ICAl CROSS-SECTION
A 2-DIHENSIONAl STRAIN ASSUHPlION IN kHICH THE
PARTIClES DEFORM IN ONE PlANE AND REMAIN THAI PlANE
PROBLEM
PRONATAION
PROPERTIES
PROXIMAL
A HAlHEHATICAL MODEL WHICH HAS HORE UNKNOlNS [HAN
EQUATIONS TO SOlVE FOR THESE UNKNOINS
rHE FREtUENCY AT dHICH A SYSrEH RESONATES OR HAS
LAR6E AMPLITUDES OR DISPlACEHENTS
RESPONSE
RHEOL06ICAl
AN ASSUMPTION IS HADE THAT THE BODY SE8HEN! [S
RI6ID OR NON-DEFORHABlE
OCR for page 39
39
Rae
s
SEE
SIR
star
STAT EOUIL
STRUCT OPT TECH
SUP
SUPP
SYN
[END
THOR
r-~
TRAB
TRANSVERSELY ISOTROPIC
OR TRANS ISOf
VAR
VERT
VERIEB
~1
RO [Al ION
STATIC
SEGhENT
SIMULATION
STATIC OR STATICALLY
PRINCIPLES OF STATIC EQUILIBRIUM HERE
USED TO fORHUlATE THE MODEL
STRUCTURAL OPTIHIlATION TECHNIQUES
SUPINATION
SUPPORT
SYHHEIRIC OR SYHHEIRY
TENDON
THORAX OR [HORACIC
TEN PORAL -HAND I B AL AR
TRABECULAR
- fORH Of ANISOTROPY FOR CHICK 5 JO 6 DIFFERENT
MATERIAL CONSTANTS ARE NEEDED JO DESCRIBE THE
RESPONSE OF THE MATERIAL
VARIATION
VERTICAL
VERTEBRAL
WITH
OCR for page 40
40
a universal mode} that is applicable in a variety of situations.
This mode! should accurately predict the loading on the body
caused by both internal and external forces and should be capable
of evaluating "wear and tear" of the body under realistic (static
as well as dynamic three-dimensional) conditions. Such a mode}
should be adaptable to a variety of situations. The same mode}
should be able to simulate gait and weight lifting and perform a
variety of human tasks.
To achieve such a goal, several areas of mode! improvement
and development are needed. More data are needed to describe the
material and functional properties of body tissues. These findings
should be incorporated into analyses that investigate the aging
as wed as the time- and frequency-dependent repetitive loading
effects of loads exerted on the body. The properties of bone must
also be incorporated into models that are used for ergonomic
purposes. More specifically, for spinal models, investigation of the
load-bearing role of the articular facets ~ needed to understand
low back pain etiology.
For bone stress analysis, the most promising mode} is finite-
element analysis, which can mode} the irregular geometry and the
composite nature of bone. Validation against experimental data
continues to present problems. Roh~xnann et al. (1982), Hunker et
al. (1981) and Hakim and King (1979), however, have attempted
such a validation. There continues to be a lack of data on ma-
terial properties and a large variation in such properties for bi-
ological materials. The problem is made more complex because
of anisotropy, inhomogeneity, and nonlinearity. Experimental re-
search and clinical application of the models are needed to further
advance the modeling effort. One area for further research is that
of developing a capability for a variation of mode} geometry w~th-
out a complete respecification of nodal coordinates. I.ewis et al.
(1980) proposed such a scaling method for femoral models.
The analogy of the rigid beam link should be investigated.
Instead of viewing the body as a set of rigid links, perhaps a
semiflexible spinal column can provide snore accurate assessments
of the lifting of loads on the body.
The modeling of joints and human locomotion (single and
multiple joints) is aimed primarily at predicting forces In mum
cles, ligaments, and bone contact. This can serve a variety of
needs, such as prosthesis design, treatment and diagnosis of mus-
culoskeletal diseases, rehabilitation, and quantification of normal
OCR for page 41
41
function. There Is very little evidence, however, that current mod-
els are able to calculate these forces accurately. The measurement
of these forces in viva is extremely difficult, and therefore, the
need exists to develop experimental techniques and transducers
to verify the analytical results. Inferences from time domain cor-
relations of muscle forces with EMG activity are at best a crude
indication of validity. One of the major problems with this area
of research Is the choice of appropriate objective functions to solve
a redundant problem. It does not fad within the deterministic
realm of mechanics and requires physiological data that are, as
yet, unavailable. The hypothesis that an objective function indeed
exists needs to be proven before further advances can be made. A
secondary problem concerns the use of linear optimization tech-
niques. The limitations of a linear analysis are implicit in their
use and should be recognized.
Whole-body models can now incorporate three-dimensional
activity as well as motion. The development of these modem over
the years has progressed from those based on pure Newtonian
mechanics to optimization theory to control theory. The control
theory mode} by Hatze (1977) appears to simulate the rate and re-
cruitment coding of the muscles during the performance of a task.
Unfortunately, when the predictive power of the models increases,
the complexity of the mode} also increases dramatically. Hence,
a trade-off must occur between mode} complexity and the degree
of accuracy that is needed to model a situation for ergonomic
purposes.
An area which remains untouched by biomechanical model-
ers is that of modeling the cognitive link. People, as information
processors, possess the ability to modify the interaction with the
musculoskeletal system. Under circumstances of great stress or
during life-threatening situations, people can shor~circuit inter-
nal protective mechanisms and are capable of exhibiting nearly
"superhumans traits. There ~ also an awareness that the "psycho-
logical factors can become dominant In times of illness, as shown
by treatment with a placebo. Additional experimental research is
needed on these issues so that the cognitive control process can be
evaluated and eventually included in biomechanical modem. Pope
et al. (1980) have begun to explore such a link between personality
traits and biomechanical behavior.
It is clear that much research is needed to achieve the goal
of producing a universal biomechanical model. Progress has been
OCR for page 42
42
slow over the years. Basically, it appears that progress in the area
of biomechanical modeling ~ now limited by a basic understand-
ing of the body rather than by computational ability. The current
state of modeling will advance when advances in basic understand-
ing are achieved and better validation methods are developed.
In addition, many of the limitations in existing biomechanical
models are related to incomplete or unrealistic data inputs into
the model. The problems include nonrigid or nonuniform links,
effects of dynamic action, internal loading including antagonistic
muscle action, comparison data for cumulative trauma limits, and
cognitive links.
furthermore, modem based on motion kinetics alone provide
an inadequate description of a person who is operating equipment
in a real-world environment. The human operator's need and
ability to adapt the dynamic behavior of the limbs ~ not included
in current models. A model of the biomechanical system that uses
single values for its dynamic parameters such as muscle stiffness or
viscosity is unrealistic. A fixed-parameter mode} cannot be applied
reliably in situations other than those for which it was calibrated.
Deterrn~nation of the difference between the net reaction forces
at a given body joint and the actual internal loads (e.g., those
generated by the antagonistic muscle groups that are involved) ~
essential to a complete biomechanical analysis of a strain that has
an impact on the system. Predictions of internal loads usually
incorporate simplistic optimizing assumptions, for example, that
minnnal antagonistic muscle activity ~ used in performing a task.
If the performance is not governed by the assumptions, the actual
internal loads can be much higher than the predicted values.
Finally, existing biomechanical models do not address the
problem of repeated activities over a period of tune, and hence,
physiological aspects such as fatigue are not considered.
Representative terms from entire chapter:
objective function
