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    Use of a Hill-Based Muscle Model in the Fast Orthogonal Search Method to Estimate Wrist Force and Upper Arm Physiological Parameters

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    Date
    2008-10-30
    Author
    Mountjoy, Katherine
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    Abstract
    Modelling of human motion is used in a wide range of applications.

    An important aspect of accurate representation of human movement is

    the ability to customize models to account for individual

    differences. The following work proposes a methodology using

    Hill-based candidate functions in the Fast Orthogonal Search (FOS)

    method to predict translational force at the wrist from flexion and

    extension torque at the elbow. Within this force estimation

    framework, it is possible to implicitly estimate subject-specific

    physiological parameters of Hill-based models of upper arm muscles.

    Surface EMG data from three muscles of the upper arm (biceps

    brachii, brachioradialis and triceps brachii) were recorded from 10

    subjects as they performed isometric contractions at varying elbow

    joint angles. Estimated muscle activation level and joint kinematic

    data (joint angle and angular velocity) were utilized as inputs to

    the FOS model. The resulting wrist force estimations were found to

    be more accurate for models utilizing Hill-based candidate

    functions, than models utilizing candidate functions that were not

    physiologically relevant. Subject-specific estimates of optimal

    joint angle were determined via frequency analysis of the selected

    FOS candidate functions. Subject-specific optimal joint angle

    estimates demonstrated low variability and fell within the range of

    angles presented in the literature.
    URI for this record
    http://hdl.handle.net/1974/1570
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    • Department of Electrical and Computer Engineering Graduate Theses
    • Queen's Graduate Theses and Dissertations
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