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

---------------------------------------------------------------