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Body segment parameters

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  • Body segment parameters

    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

    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

    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: