Using multi-objective optimization, we develop a new human performance measure for direct optimizationbased posture prediction that incorporates three key factors associated with musculoskeletal discomfort: 1) the tendency to move different segments of the body sequentially, 2) the tendency to gravitate to a comfortable neutral position, and 3) the discomfort associated with moving while joints are near their respective limits. This performance measure operates in real-time and provides realistic postures. The results are viewed using Santos™, an advanced virtual human, and they are validated using motion-capture. This research lays groundwork for studying how and why humans move as they do.


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    Title :

    A New Discomfort Function for Optimization-Based Posture Prediction


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    2005 Digital Human Modeling for Design and Engineering Symposium ; 2005



    Publication date :

    2005-06-14




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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