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Myoskeletal Inverse Dynamics

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  • Myoskeletal Inverse Dynamics

    *This message was transferred with a trial version of CommuniGate(tm) Pro*
    I have been following with great interest the recent discussion initiated by
    Prof. Hatze. The assessment of neuromuscular disorders (particularly in
    children) is probably the dominant clinical application of motion analysis.
    The vision Prof. Hatze presented earlier today, of using musculoskeletal
    models to design individualized optimal treatment strategies for children
    with neuromuscular disorders, has been the "holy grail" of clinical gait
    analysis for many years. I remember discussing this vision in the 1980's
    with some of the early advocates of automated clinical gait analysis for the
    treatment of cerebral palsy in the U.S. (e.g. Jim Gage, David Sutherland).
    We acknowledged the limitations of the models and technology available then,
    but we were convinced that these problems would be solved over time. In
    fact, most of the problems we KNEW about 20 years ago have been solved - the
    data is much better (though arguably still far from perfect), the computers
    are fast enough, the musculoskeletal models are far more comprehensive, and
    better subject-specific anatomy/geometry is available from vastly improved
    medical imaging. Some of the results are visible - motion analysis and
    musculoskeletal modeling have clearly lead to better understanding and
    improved outcome of treatment for children with cerebral palsy. And yet, it
    seems that the goal of patient-specific treatment optimization and outcome
    prediction for individuals with neuromuscular disorders remains a distant

    Prof. Hatze rightly argues that further improvements in all of the areas
    listed above are needed. He also addresses our limited understanding of the
    performance criteria the nervous system uses to select a motor control
    strategy for a specific task. This, in my opinion, is one of the areas
    where we are significantly lacking. We are far from fully understanding the
    criteria the intact neuromuscular control system utilizes for optimizing
    muscle activation during essential motor tasks. Neuromuscular disorders
    (such as spastic diplegia) alter essentially all aspects of the motor
    control system (sensors, actuators, controllers); this may render many of
    our "normal" modeling and control strategy assumptions of limited value.
    New experimental and modeling paradigms may be needed to sufficiently expand
    our knowledge in this area.

    Even as we get closer to addressing these problems, we may run headfirst
    into another. Our models for motion analysis have traditionally been
    targeted at the anatomy, physiology and mechanics of the body and its
    neuromusculoskeletal components. For example, in our modeling world we
    typically assume that if we know all of the mechanical properties of a
    tendon (geometry, viscoelastic properties, etc), we can predict how it will
    behave in a given biomechanical environment. Many of us choose to ignore
    the biological reality that no living tissue has static mechanical
    properties. We make this choice even though we are generally aware that
    bones, tendons and muscles all change their properties with changes in their
    mechanical and/or biological environment - perhaps the alternative has been
    too complex to consider (or at least to model). This may, however, be a
    particularly limiting assumption in children, since a young, growing tissue
    is more sensitive to changes in its environment than the corresponding
    tissue in an adult. Say, for example, a preoperative gait analysis is
    performed on a 7 year old child, who then undergoes a complex surgical
    procedure. The goal is to optimize gait performance, as assessed during a
    follow-up gait analysis one year later. How much do the geometry and
    characteristics of the bones, muscles, tendons, nervous system, etc. of a
    young child change in a year? [personal note - As a parent of such a child,
    I would say a lot!] How might these changes have been affected/altered by
    the procedures that were performed? How would the resulting changes affect
    predictions of optimal movement? These are questions for which we currently
    have no good answers. Thus, I would argue that a comprehensive model to
    predict the optimal treatment for a child would need to somehow incorporate
    prediction of growth and tissue remodeling. This would add a whole new
    layer of complexity, especially for those who argue for a single,
    comprehensive modeling framework capable of addressing a wide variety of

    Furthermore, the problem is not limited to neuromuscular disorders of the
    young. Biological adaptation is a known issue for natural or biologically
    engineered tissue replacements. For example, there is strong evidence
    suggesting that the autologous tendon grafts used to replace failed anterior
    cruciate ligaments undergo significant long-term biological remodeling after
    they are placed in the knee capsule, with resultant changes in mechanical
    properties. And yet, models (mathematical/computer and cadaver) used to
    study this procedure generally do not (or cannot) account for these changes.
    The extent to which this simplification limits the value of these models is
    difficult to assess with currently available data (though it would depend to
    some extent on the goals/hypotheses of the modeler).

    Perhaps when our models were crude and generic, biological adaptations were
    not worth considering. But, as the other aspects of musculoskeletal
    modeling continue to improve, I believe that the importance of modeling
    biological responses and adaptations in musculoskeletal tissues will
    continue to emerge. This is hardly a new direction for research - there is
    a great deal of active and historical research in tissue growth and
    remodeling. But, biological growth/adaptation has not traditionally been
    investigated within the framework of in-vivo studies of human movement.
    This presents both a tremendous challenge and a real opportunity for
    intelligently designed research to investigate biological adaptations and
    their impact on in-vivo human movement biomechanics.

    Please pardon my rambling on, but I hope these thoughts add fuel to the
    current discussion. I am very interested in others' opinions on these

    Scott Tashman

    __________________________________________________ ____
    Scott Tashman, Ph.D.

    Head, Motion Analysis Section Assistant Professor
    Bone and Joint Center Department of Orthopaedics
    Henry Ford Hospital School of Medicine
    2799 W. Grand Blvd, ER2015 Case Western Reserve University
    Detroit, MI 48202

    Voice: (313) 916-8680
    FAX: (313) 916-8812
    __________________________________________________ ____

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