Dear List Members,
First, many thanks for the overwhelming response to those who reacted to
the problem statement of the above topic.
Although any contribution is welcome, it is necessary to keep the
discussion focused on the current topic, as has been pointed out
recently by Dr. Leardini and Dr. van den Bogert. There is no need to
deviate from the topic currently under discussion because the next
topics planned for the discussion forum are (abbreviated) "HUMAN BODY
MODELS INCLUDING TISSUE ANALOGS", "SKELETAL MUSCLE MODELS",
"IDENTIFICATION OF NEUROMYOSKELETAL PERFORMANCE CRITERIA AND THE
MYOSKELETAL INDETERMINACY PROBLEM", and "DEVELOPMENT OF NOVEL METHODS
FOR SUBJECT-SPECIFIC PARAMETER IDENTIFICATION". These topics cover a
wide range of problems occurring in HUMAN MUSCULOSKELETAL BIOMECHANICS
which, as should be remembered, is the general theme of the present
sequence of discussion sessions.
This does, however, not mean that other topics outside this range could
not be debated but this should be done at a later stage to avoid
discussions drifting out of hand. Virtually all contributions submitted
until now fit into one or more of the above mentioned topic categories
except, perhaps, Dr. Duda's microscopical cell-cell interactions. But
even molecular dynamics is part of the current discussion series because
the elucidation and modeling of the power stroke generation within the
muscle fiber myosin-subfragment-1 unit after association with actin is
presently a "hot topic" in skeletal muscle modeling.
I shall now briefly comment on the opinions posted until Monday, 14
January. The views expressed are very diverse and range from rather
traditional and conservative to enthusiastic, visionary, and open for
new approaches.
The emphasis in the discussions lay undoubtedly on CLINICAL GAIT
ANALYSIS. The CONSERVATIVE VIEW seems to be that present gait analysis
procedures and models are, on the whole, satisfactory and do not really
need to be improved substantially. It was suggested that accelerations
are small in pathological gait and therefore inverse dynamics solutions
in clinical gait analysis are trustworthy so that clinicians need not
worry unduly. Concern was expressed that the present adequate models are
not appropriately incorporated into clinical practice, that measures of
validity of presently applied methods are missing, that the estimation
of joint centers (or rather axes) of rotation are the single greatest
error source, and that both bioengineers and clinicians lack
biomechanical understanding.
The discussants expressing more PROGRESSIVE VIEWS recognise the
deficiencies of currently used models and methods in clinical gait
analysis. A need for improvements is seen in the calculation of joint
kinetics, in the presently used anthropomorphic models, in the
estimation of joint axes locations, in the computation of moment arms,
and in the development of new techniques for determining
subject-specific model parameter values. In contrast, the necessarity of
detemining individually and adequately for each subject the inertial and
anthropometric segment parameters was no issue for the conservative gait
analysts.
Most interestingly, some of the (apparently) younger discussants
enthusiastically proposed visionary concepts for future biomechanical
modeling which strongly agree with my own views on Second Generation
Biomechanics. A basic concept, relating to the objectives of human
motion analysis, will be briefly discussed below. Congratulations to
these colleagues of the younger generation. My hope is that they will be
the ones who implement the next phase in the development of
biomechanics.
In conclusion, I would like to express MY PERSONAL OPINION on the views
just summarized. It should be clear that motion analysis (which I feel
is a more appropriate term than "movement" analysis) is not restricted
to the analysis of pathological gait and sports motions but, quite
generally, is applicable to any type of human motion such as
(predominantly passive) car crash victim behavior, work motions,
reconstruction of accidents, observation of non-gait-rehabilitation
processes, etc. On the other hand, there is no clear definition of the
term "motion analysis". If taken to be opposite of motion synthesis
(synonymous with motion simulation or forward dynamics) then motion
analysis presupposes the use of the inverted dynamical system equations
(inverse dynamics) and therefore can not consist of procedures that
compare kinematic quantities (such as joint angle histories) only.
Turning now to the FUNDAMENTAL PROBLEM OF MYOSKELETAL INVERSE DYNAMICS
and its implications it should be realized that this formulation
provides us with a means of assessing the VALIDITY of a specific inverse
dynamics model used for motion analysis. In fact, if the dynamic body
model is formulated as a multi-body system with a fictitious hinge at
the body center and having a fixed number of degrees of freedom, and
external constraints are accounted for by additional algebraic
equations, then this formulation results in a combined system of
differential-algebraic equations (which is state of the art). In this
case, the first three equations of the inverted system can be used to
compute the three spatial components of the ground reaction forces as
would be predicted by the inverse dynamics model for a specific motion
pattern used as model input. Obviously, these model-predicted ground
reaction force histories can be compared with the ones actually measured
by the force plates. Under the (justified) assumption that the measured
ground reaction forces resulting from the dynamics of the motion of the
real biosystem (the patient or subject) are reasonably accurate, the
discrepancy between model response and that of the real biosystem is a
measure for the validity and quality of the model and the input data.
Small discrepancies imply good models (and input data), large
discrepancies mean the opposite. A typical example of such an inverse
dynamics model validation, showing dramatic model deficiencies which
usually remain undetected, can be found in Hatze, H. (January 2002): The
fundamental problem of myoskeletal inverse dynamics and its
implications, Journal of Biomechanics 35/1, pp. 109-115. There it can be
seen that this problem certainly did not originate from a purist's brain
hidden in an academic back room or an ivory tower far removed from
reality, but from every-day practical work in the motion research
laboratory.
It is also not too surprising that, as one discussant remarked,
"...NATURE DOES NOT SEEM TO BOTHER ABOUT THIS FUNDAMENTAL PROBLEM. Even
the simplest animals (including humans) are able to consistently
reproduce their movement patterns ...". Apart from the fact that I (and
probably many others) sadly lack the feeling of belonging to the class
of simplest animals, do these creatures most likely not engage in
extensive model building and inverse dynamics evaluations, and therefore
miss out on the opportunity and the intellectual pleasure of coming
across this problem.
Finally, I would like to respond to the accusation made by some
discussants that frequently in biomechanical research the formulation of
SPECIFIC HYPOTHESES, or the establishing and utilisation of simplifying
principles, is missing. This is, unfortunately, true to a large extent
for some areas of biomechanical research conducted today and is as
unacceptable as it is in any other scientific discipline. At the
beginning of any investigation there should always be a clear concept of
the processes involved and the aims to be pursued.
As far as the OBJECTIVES OF MOTION ANALYSIS are concerned, MY BASIC
HYPOTHESIS underlying and guiding all my research and publications on
active motions over the past 35 years, was always the postulated
TELEOLOGICAL BEHAVIOR OF BIOSYSTEMS AS THE OVERRIDING PRINCIPLE which
determines the form of any type of active (but not passive) human
motion. More specifically, I am convinced that there ALWAYS exists a
PERFORMANCE CRITERION, however complex, which the biosystem (the
subject) attempts to minimise or maximise in the execution of a given
task. In some cases we know these criteria, in others we don't. It has,
for instance, been shown that if a person is to walk a long distance
without being under time pressure, it will adopt a combination of step
length and step frequency that minimizes the metabolic energy expended.
In other words, the nervous system generates optimal neural control
patterns that control the muscles in such a way that a (in a specific
sense) optimal motion results. This is then the "best" motion under the
given circumstances and for a specific individual.
Suppose that such an OPTIMAL TARGET MOTION is available for a given
individual, for instance by using the optimal control solution of an
adequate human neuromusculoskeletal system model. Then the objective of
motion analysis is to compare the recorded present-status motion of the
subject with the optimum, investigate the reasons for possible
discrepancies and, ideally, implement measures (treatment) for
improvement until a satisfactory status has been achieved.
At present, this is wishful thinking. Neither do we, in general, know
the performance criteria the nervous system uses (which is one of the
topics to be discussed soon), nor do we have sufficiently complex and
adequate simulation models of the human neuromusculoskeletal system
(two other discussion topics, including skeletal muscle modeling), or
proper methods for determining the necessary subject-specific parameter
sets to individualize the model (also a discussion topic). Analogous
remarks apply to inverse dynamics.
If, however, such comprehensive models and methods could be developed,
their utilisation would open up entirely new opportunities. An EXAMPLE
OF CLINICAL APPLICATION could be the following. A spastic child exhibits
the typical pathological gait pattern characteristic of this condition.
The child's individual set of anthropometric, inertial, articular,
myodynamic, and myocybernetic parameter values is determined
experimentally and used to individualize the general simulation model.
The performance criterion to be minimized is the (appropriately defined)
"difference" between the currently observed spastic gait pattern and a
"normal" gait pattern. This is a combined optimal control and parameter
optimization problem in which certain anthropometric and possibly
myodynamic parameters are changed as part of the optimization procedure,
as are the neural inputs to the skeletal muscles. The result could be a
modified (but for the target gait pattern optimal) parameter set
requiring, for instance, for its practical implementation the surgical
lenghtening of certain muscle groups (such as the triceps surae) as well
as the surgical translocation of specific muscle origins and (or)
insertions. In addition, the optimization procedure would yield the
optimal, now "normal looking" gait pattern specific for this child.
Clinical gait analysis would then be used to continually observe during
the rehabilitation phase the post-surgical progress toward the new
optimal and normal gait pattern.
This scenario may sound like a somewhat futuristic vision. I am,
however, convinced that such developments could be successfully
completed by a combined effort of the biomechanics community. Fairly
advanced submodels and parameter identification techniques exist already
and are used routinely.
Herbert Hatze
************************************************** ******
Prof. Dr. Herbert Hatze
Head, Department and Laboratory of Biomechanics, ISW,
University of Vienna
Auf der Schmelz 6 Tel: + 43 1 4277 48880
A-1150 WIEN Fax: + 43 1 4277 48889
AUSTRIA e-mail: herbert.hatze@univie.ac.at
************************************************** ******
---------------------------------------------------------------
To unsubscribe send SIGNOFF BIOMCH-L to LISTSERV@nic.surfnet.nl
For information and archives: http://isb.ri.ccf.org/biomch-l
---------------------------------------------------------------
First, many thanks for the overwhelming response to those who reacted to
the problem statement of the above topic.
Although any contribution is welcome, it is necessary to keep the
discussion focused on the current topic, as has been pointed out
recently by Dr. Leardini and Dr. van den Bogert. There is no need to
deviate from the topic currently under discussion because the next
topics planned for the discussion forum are (abbreviated) "HUMAN BODY
MODELS INCLUDING TISSUE ANALOGS", "SKELETAL MUSCLE MODELS",
"IDENTIFICATION OF NEUROMYOSKELETAL PERFORMANCE CRITERIA AND THE
MYOSKELETAL INDETERMINACY PROBLEM", and "DEVELOPMENT OF NOVEL METHODS
FOR SUBJECT-SPECIFIC PARAMETER IDENTIFICATION". These topics cover a
wide range of problems occurring in HUMAN MUSCULOSKELETAL BIOMECHANICS
which, as should be remembered, is the general theme of the present
sequence of discussion sessions.
This does, however, not mean that other topics outside this range could
not be debated but this should be done at a later stage to avoid
discussions drifting out of hand. Virtually all contributions submitted
until now fit into one or more of the above mentioned topic categories
except, perhaps, Dr. Duda's microscopical cell-cell interactions. But
even molecular dynamics is part of the current discussion series because
the elucidation and modeling of the power stroke generation within the
muscle fiber myosin-subfragment-1 unit after association with actin is
presently a "hot topic" in skeletal muscle modeling.
I shall now briefly comment on the opinions posted until Monday, 14
January. The views expressed are very diverse and range from rather
traditional and conservative to enthusiastic, visionary, and open for
new approaches.
The emphasis in the discussions lay undoubtedly on CLINICAL GAIT
ANALYSIS. The CONSERVATIVE VIEW seems to be that present gait analysis
procedures and models are, on the whole, satisfactory and do not really
need to be improved substantially. It was suggested that accelerations
are small in pathological gait and therefore inverse dynamics solutions
in clinical gait analysis are trustworthy so that clinicians need not
worry unduly. Concern was expressed that the present adequate models are
not appropriately incorporated into clinical practice, that measures of
validity of presently applied methods are missing, that the estimation
of joint centers (or rather axes) of rotation are the single greatest
error source, and that both bioengineers and clinicians lack
biomechanical understanding.
The discussants expressing more PROGRESSIVE VIEWS recognise the
deficiencies of currently used models and methods in clinical gait
analysis. A need for improvements is seen in the calculation of joint
kinetics, in the presently used anthropomorphic models, in the
estimation of joint axes locations, in the computation of moment arms,
and in the development of new techniques for determining
subject-specific model parameter values. In contrast, the necessarity of
detemining individually and adequately for each subject the inertial and
anthropometric segment parameters was no issue for the conservative gait
analysts.
Most interestingly, some of the (apparently) younger discussants
enthusiastically proposed visionary concepts for future biomechanical
modeling which strongly agree with my own views on Second Generation
Biomechanics. A basic concept, relating to the objectives of human
motion analysis, will be briefly discussed below. Congratulations to
these colleagues of the younger generation. My hope is that they will be
the ones who implement the next phase in the development of
biomechanics.
In conclusion, I would like to express MY PERSONAL OPINION on the views
just summarized. It should be clear that motion analysis (which I feel
is a more appropriate term than "movement" analysis) is not restricted
to the analysis of pathological gait and sports motions but, quite
generally, is applicable to any type of human motion such as
(predominantly passive) car crash victim behavior, work motions,
reconstruction of accidents, observation of non-gait-rehabilitation
processes, etc. On the other hand, there is no clear definition of the
term "motion analysis". If taken to be opposite of motion synthesis
(synonymous with motion simulation or forward dynamics) then motion
analysis presupposes the use of the inverted dynamical system equations
(inverse dynamics) and therefore can not consist of procedures that
compare kinematic quantities (such as joint angle histories) only.
Turning now to the FUNDAMENTAL PROBLEM OF MYOSKELETAL INVERSE DYNAMICS
and its implications it should be realized that this formulation
provides us with a means of assessing the VALIDITY of a specific inverse
dynamics model used for motion analysis. In fact, if the dynamic body
model is formulated as a multi-body system with a fictitious hinge at
the body center and having a fixed number of degrees of freedom, and
external constraints are accounted for by additional algebraic
equations, then this formulation results in a combined system of
differential-algebraic equations (which is state of the art). In this
case, the first three equations of the inverted system can be used to
compute the three spatial components of the ground reaction forces as
would be predicted by the inverse dynamics model for a specific motion
pattern used as model input. Obviously, these model-predicted ground
reaction force histories can be compared with the ones actually measured
by the force plates. Under the (justified) assumption that the measured
ground reaction forces resulting from the dynamics of the motion of the
real biosystem (the patient or subject) are reasonably accurate, the
discrepancy between model response and that of the real biosystem is a
measure for the validity and quality of the model and the input data.
Small discrepancies imply good models (and input data), large
discrepancies mean the opposite. A typical example of such an inverse
dynamics model validation, showing dramatic model deficiencies which
usually remain undetected, can be found in Hatze, H. (January 2002): The
fundamental problem of myoskeletal inverse dynamics and its
implications, Journal of Biomechanics 35/1, pp. 109-115. There it can be
seen that this problem certainly did not originate from a purist's brain
hidden in an academic back room or an ivory tower far removed from
reality, but from every-day practical work in the motion research
laboratory.
It is also not too surprising that, as one discussant remarked,
"...NATURE DOES NOT SEEM TO BOTHER ABOUT THIS FUNDAMENTAL PROBLEM. Even
the simplest animals (including humans) are able to consistently
reproduce their movement patterns ...". Apart from the fact that I (and
probably many others) sadly lack the feeling of belonging to the class
of simplest animals, do these creatures most likely not engage in
extensive model building and inverse dynamics evaluations, and therefore
miss out on the opportunity and the intellectual pleasure of coming
across this problem.
Finally, I would like to respond to the accusation made by some
discussants that frequently in biomechanical research the formulation of
SPECIFIC HYPOTHESES, or the establishing and utilisation of simplifying
principles, is missing. This is, unfortunately, true to a large extent
for some areas of biomechanical research conducted today and is as
unacceptable as it is in any other scientific discipline. At the
beginning of any investigation there should always be a clear concept of
the processes involved and the aims to be pursued.
As far as the OBJECTIVES OF MOTION ANALYSIS are concerned, MY BASIC
HYPOTHESIS underlying and guiding all my research and publications on
active motions over the past 35 years, was always the postulated
TELEOLOGICAL BEHAVIOR OF BIOSYSTEMS AS THE OVERRIDING PRINCIPLE which
determines the form of any type of active (but not passive) human
motion. More specifically, I am convinced that there ALWAYS exists a
PERFORMANCE CRITERION, however complex, which the biosystem (the
subject) attempts to minimise or maximise in the execution of a given
task. In some cases we know these criteria, in others we don't. It has,
for instance, been shown that if a person is to walk a long distance
without being under time pressure, it will adopt a combination of step
length and step frequency that minimizes the metabolic energy expended.
In other words, the nervous system generates optimal neural control
patterns that control the muscles in such a way that a (in a specific
sense) optimal motion results. This is then the "best" motion under the
given circumstances and for a specific individual.
Suppose that such an OPTIMAL TARGET MOTION is available for a given
individual, for instance by using the optimal control solution of an
adequate human neuromusculoskeletal system model. Then the objective of
motion analysis is to compare the recorded present-status motion of the
subject with the optimum, investigate the reasons for possible
discrepancies and, ideally, implement measures (treatment) for
improvement until a satisfactory status has been achieved.
At present, this is wishful thinking. Neither do we, in general, know
the performance criteria the nervous system uses (which is one of the
topics to be discussed soon), nor do we have sufficiently complex and
adequate simulation models of the human neuromusculoskeletal system
(two other discussion topics, including skeletal muscle modeling), or
proper methods for determining the necessary subject-specific parameter
sets to individualize the model (also a discussion topic). Analogous
remarks apply to inverse dynamics.
If, however, such comprehensive models and methods could be developed,
their utilisation would open up entirely new opportunities. An EXAMPLE
OF CLINICAL APPLICATION could be the following. A spastic child exhibits
the typical pathological gait pattern characteristic of this condition.
The child's individual set of anthropometric, inertial, articular,
myodynamic, and myocybernetic parameter values is determined
experimentally and used to individualize the general simulation model.
The performance criterion to be minimized is the (appropriately defined)
"difference" between the currently observed spastic gait pattern and a
"normal" gait pattern. This is a combined optimal control and parameter
optimization problem in which certain anthropometric and possibly
myodynamic parameters are changed as part of the optimization procedure,
as are the neural inputs to the skeletal muscles. The result could be a
modified (but for the target gait pattern optimal) parameter set
requiring, for instance, for its practical implementation the surgical
lenghtening of certain muscle groups (such as the triceps surae) as well
as the surgical translocation of specific muscle origins and (or)
insertions. In addition, the optimization procedure would yield the
optimal, now "normal looking" gait pattern specific for this child.
Clinical gait analysis would then be used to continually observe during
the rehabilitation phase the post-surgical progress toward the new
optimal and normal gait pattern.
This scenario may sound like a somewhat futuristic vision. I am,
however, convinced that such developments could be successfully
completed by a combined effort of the biomechanics community. Fairly
advanced submodels and parameter identification techniques exist already
and are used routinely.
Herbert Hatze
************************************************** ******
Prof. Dr. Herbert Hatze
Head, Department and Laboratory of Biomechanics, ISW,
University of Vienna
Auf der Schmelz 6 Tel: + 43 1 4277 48880
A-1150 WIEN Fax: + 43 1 4277 48889
AUSTRIA e-mail: herbert.hatze@univie.ac.at
************************************************** ******
---------------------------------------------------------------
To unsubscribe send SIGNOFF BIOMCH-L to LISTSERV@nic.surfnet.nl
For information and archives: http://isb.ri.ccf.org/biomch-l
---------------------------------------------------------------