Hello All,

Recently I had the occasion to talk to a number of people from Europe and

the US who have been or are currently involved in mathematical modelling

of human motion. In the course of the conversations we talked about the

estimation of body segment mass and inertia parameters and I found that

no one that I talked to knew about a US Air Force report from 1981 which

is fairly extensive in its techniques for estimating segment data. Thus,

here is the relavent information for those who may interested in obtaining

a copy as well as the abstract and a brief summary (i.e., a subjective

evaluation) of how it has worked out for my application, a large program

to analyze kinematics, kinetics, energetics, and muscle dynamics during

human motion.

I'm not sure where you can actually order this report (it was given to

me by Necip Berme and he is on sabbatical this year so I can't find out

how he got it). If someone does know, please post a message as to how it

is done.

Report #: AFAMRL-TR-80-119 (Approved for public release)

December 1980, p. 109 (Unlimited distribution)

Title: Anthropometric Relationships of Body and Body Segment Moments

of Inertia

Authors: *McConville, J.T., *Churchill, T.D., +Kaleps, I., +Clauser, C.E.,

~Cuzzi, J.

* Anthropology Research Project, Inc.

Yellow Springs, Ohio 45387 USA

+ Air Force Aerospace Medical Research Laboratory

Aerospace Medical Division

Air Force Systems Command

Wright-Patterson Air Force Base, Ohio 45433 USA

~ Texas Institute for Rehabilitation and Research

Houston, Texas 77030

Abstract:

This report documents the results of a study aimed at demonstrating that mass

distribution properties of the human body and its segments can be predicted

from anthropometric dimensions. Investigators combined stereophotometric

and anthropometric techniques to measure 31 male subjects. Bodies were

photographically segmented into 24 parts and their volume, centers of volume

and principal moments were measured about the three principal axes of inertia

which were established with reference to anatomical axis systems based on

easily located body landmarks.

Seventy-five body size variables were measured anthropometrically and an

additional 10 dimensions were derived from the measured variables. Multiple

regression equations were devised for the total body and for each of the

segments using the most highly correlated variables on each segment and

stature and weight for determining volume and principal moments of inertia.

Included is a brief review of the literature with emphasis on those studies

by authors which provide the rationale for the validity of the stereophoto-

metric method in determining mass distribution properties of living subjects.

The data analysis section provides tables illustrating each of the segments

and their axis systems, the segmental data established in this study, and

a series of regression equations estimating volume and principal moments

from anthropometric measurements

Comment:

The most unique feature of the methods used here is the tranformation

from an anatomically derived coordinate system (CS) to the segment principal

inertia CS located at the segment center of volume. This allows the

determination of a CS from easy to find and measure anatomic points. This

feature, in my opinion, is flawed unfortunately. The authors have gone

to considerable trouble to derive regression equations for the segment

parameters but there are no such equations for the transformation from the

anatomic CS to the principal inertia CS. Instead the mean and standard

deviation of the location of the volume center from the anatomic CS center

for all subjects is given. There is no subject specificity available.

The same applies to the rotation from the anatomic CS to the principal inertia

CS, which is given in terms of yaw-pitch-roll euler angles. The regression

equations on the other hand are well done. For most segments there are

15 to 20 different combinations of anthropometric measurements whose resulting

equation coefficients are given along with the multiple correlation coefficient

and the standard error of estimate. Most of the standard error of estimates

are around 10% of the mean of the segment parameter. Since only the volume

and moment of inertia of the volume are generated it is necessary to assume

a homogenous distribution of mass within the segment and use this to calculate

the mass and mass moments of inertia. These densities are discussed in

the report. Lastly, this study has the problem that just every study I've

looked at that deals with estimating segment inertia parameters (about 10

to 15 - experimentally oriented studies, not the computational studies

such as those by Hatze and Vaughan) has - Namely, the data used was collected

from adults and primarily males (in this case all males). We deal with

children having neuromuscular disorders just as often as adults and it would

be nice to have proper data on their segment parameters (I remember reading

a brief summary which looked at some Japanese children in one of the ISB

conference abstracts from a while back).

I have programmed the estimation equations in their most simple form which

uses only the height and weight of the subject to calculate the segment

parameters and then have placed the principal inertia CS using the estimates

of Dempster. It was done this way because we are interested in doing

retrospective analyses of the gait data collected by the lab over the past 8

or so years (about 1000 subjects) and these studies contain only the height and

weight of the subjects in addition to all the marker data (we use Vicon),

force plate and EMG data. For new studies we are setting up the option to

measure some of the anatomic points (there are 77 points required to get the

anatomic CS's !), but it is considerably more difficult to use this protocol

in a clinical situation where you subjects who tire easily or are uncooperative

such as childern :-). We are only using thirteen body segments so I have

combined some of the study's segment data to estimate segment parameters

using the parallel axis theorem, etc... The sum of the estimated segment

masses is approximately 10% higher than the actual weight of the subject

in every case tried so far. The effect of this difference upon kinetic

calculations, such as the intersegmental joint resultant moments and force,

has not been studied here yet, but I'll get around to it. (I'm sure others

have done this already but I can't remember any specific examples right

now, anybody care to comment ?)

One last note: I am not passing judgement upon the various methods used

to estimate segment mass-inertia parameters. The above is intended to get

others to discuss what I think is a fundamental problem in biomechanics

which has not been answered to the degree of generality that I feel it should.

The recent paper in the Journal of Biomechanics (this past spring, I can't

remember which issue) using MRI to estimate segment mass-inertia parameters

seems to indicate a possible answer as to how to get data specific to an

individual subject. But, how bullet-proof is the software ? Can it be

developed to the point that it can used everyday ? How long does an analysis

take and how much operator supervision is needed ? Will this technique

be enhanced to the point where it is practical and economical to be used

for clinical human motion analyses ? I wish those who working on these

problems the best and I hope to use the fruits of their labor in the not

too distant future. Enough said (by me), for now... :-)

What is the world coming to that people are obligated to include disclaimers

with everthing ? In that spirit, anything expressed here was not said by

anybody. Period.

Dwight Meglan, Phd-in-training & Research Engineer

Ohio State University Hosipital

Gait Analysis Laboratory

1054 Dodd Hall

471 Dodd Drive

Columbus, OH 43210 USA (614)293-3808 Email: meglan%gait1@eng.ohio-state.edu

Recently I had the occasion to talk to a number of people from Europe and

the US who have been or are currently involved in mathematical modelling

of human motion. In the course of the conversations we talked about the

estimation of body segment mass and inertia parameters and I found that

no one that I talked to knew about a US Air Force report from 1981 which

is fairly extensive in its techniques for estimating segment data. Thus,

here is the relavent information for those who may interested in obtaining

a copy as well as the abstract and a brief summary (i.e., a subjective

evaluation) of how it has worked out for my application, a large program

to analyze kinematics, kinetics, energetics, and muscle dynamics during

human motion.

I'm not sure where you can actually order this report (it was given to

me by Necip Berme and he is on sabbatical this year so I can't find out

how he got it). If someone does know, please post a message as to how it

is done.

Report #: AFAMRL-TR-80-119 (Approved for public release)

December 1980, p. 109 (Unlimited distribution)

Title: Anthropometric Relationships of Body and Body Segment Moments

of Inertia

Authors: *McConville, J.T., *Churchill, T.D., +Kaleps, I., +Clauser, C.E.,

~Cuzzi, J.

* Anthropology Research Project, Inc.

Yellow Springs, Ohio 45387 USA

+ Air Force Aerospace Medical Research Laboratory

Aerospace Medical Division

Air Force Systems Command

Wright-Patterson Air Force Base, Ohio 45433 USA

~ Texas Institute for Rehabilitation and Research

Houston, Texas 77030

Abstract:

This report documents the results of a study aimed at demonstrating that mass

distribution properties of the human body and its segments can be predicted

from anthropometric dimensions. Investigators combined stereophotometric

and anthropometric techniques to measure 31 male subjects. Bodies were

photographically segmented into 24 parts and their volume, centers of volume

and principal moments were measured about the three principal axes of inertia

which were established with reference to anatomical axis systems based on

easily located body landmarks.

Seventy-five body size variables were measured anthropometrically and an

additional 10 dimensions were derived from the measured variables. Multiple

regression equations were devised for the total body and for each of the

segments using the most highly correlated variables on each segment and

stature and weight for determining volume and principal moments of inertia.

Included is a brief review of the literature with emphasis on those studies

by authors which provide the rationale for the validity of the stereophoto-

metric method in determining mass distribution properties of living subjects.

The data analysis section provides tables illustrating each of the segments

and their axis systems, the segmental data established in this study, and

a series of regression equations estimating volume and principal moments

from anthropometric measurements

Comment:

The most unique feature of the methods used here is the tranformation

from an anatomically derived coordinate system (CS) to the segment principal

inertia CS located at the segment center of volume. This allows the

determination of a CS from easy to find and measure anatomic points. This

feature, in my opinion, is flawed unfortunately. The authors have gone

to considerable trouble to derive regression equations for the segment

parameters but there are no such equations for the transformation from the

anatomic CS to the principal inertia CS. Instead the mean and standard

deviation of the location of the volume center from the anatomic CS center

for all subjects is given. There is no subject specificity available.

The same applies to the rotation from the anatomic CS to the principal inertia

CS, which is given in terms of yaw-pitch-roll euler angles. The regression

equations on the other hand are well done. For most segments there are

15 to 20 different combinations of anthropometric measurements whose resulting

equation coefficients are given along with the multiple correlation coefficient

and the standard error of estimate. Most of the standard error of estimates

are around 10% of the mean of the segment parameter. Since only the volume

and moment of inertia of the volume are generated it is necessary to assume

a homogenous distribution of mass within the segment and use this to calculate

the mass and mass moments of inertia. These densities are discussed in

the report. Lastly, this study has the problem that just every study I've

looked at that deals with estimating segment inertia parameters (about 10

to 15 - experimentally oriented studies, not the computational studies

such as those by Hatze and Vaughan) has - Namely, the data used was collected

from adults and primarily males (in this case all males). We deal with

children having neuromuscular disorders just as often as adults and it would

be nice to have proper data on their segment parameters (I remember reading

a brief summary which looked at some Japanese children in one of the ISB

conference abstracts from a while back).

I have programmed the estimation equations in their most simple form which

uses only the height and weight of the subject to calculate the segment

parameters and then have placed the principal inertia CS using the estimates

of Dempster. It was done this way because we are interested in doing

retrospective analyses of the gait data collected by the lab over the past 8

or so years (about 1000 subjects) and these studies contain only the height and

weight of the subjects in addition to all the marker data (we use Vicon),

force plate and EMG data. For new studies we are setting up the option to

measure some of the anatomic points (there are 77 points required to get the

anatomic CS's !), but it is considerably more difficult to use this protocol

in a clinical situation where you subjects who tire easily or are uncooperative

such as childern :-). We are only using thirteen body segments so I have

combined some of the study's segment data to estimate segment parameters

using the parallel axis theorem, etc... The sum of the estimated segment

masses is approximately 10% higher than the actual weight of the subject

in every case tried so far. The effect of this difference upon kinetic

calculations, such as the intersegmental joint resultant moments and force,

has not been studied here yet, but I'll get around to it. (I'm sure others

have done this already but I can't remember any specific examples right

now, anybody care to comment ?)

One last note: I am not passing judgement upon the various methods used

to estimate segment mass-inertia parameters. The above is intended to get

others to discuss what I think is a fundamental problem in biomechanics

which has not been answered to the degree of generality that I feel it should.

The recent paper in the Journal of Biomechanics (this past spring, I can't

remember which issue) using MRI to estimate segment mass-inertia parameters

seems to indicate a possible answer as to how to get data specific to an

individual subject. But, how bullet-proof is the software ? Can it be

developed to the point that it can used everyday ? How long does an analysis

take and how much operator supervision is needed ? Will this technique

be enhanced to the point where it is practical and economical to be used

for clinical human motion analyses ? I wish those who working on these

problems the best and I hope to use the fruits of their labor in the not

too distant future. Enough said (by me), for now... :-)

What is the world coming to that people are obligated to include disclaimers

with everthing ? In that spirit, anything expressed here was not said by

anybody. Period.

Dwight Meglan, Phd-in-training & Research Engineer

Ohio State University Hosipital

Gait Analysis Laboratory

1054 Dodd Hall

471 Dodd Drive

Columbus, OH 43210 USA (614)293-3808 Email: meglan%gait1@eng.ohio-state.edu