Abstract

One of the most challenging aspects of biomechanical modelling is parameter estimation. Parameter values that define the nonlinear relations within the classic Hill-based muscle model structure have been estimated for a large number of muscles involved in movements of a number of joints. The technique used to estimate these parameters is based on combining information on muscle as a material with geometrical data on muscle-joint anatomy. The resulting relations are compatible with available human experimental data and with past modelling estimates. An estimation of the relative importance of the various synergistic muscle properties during dynamic movement tasks is also provided, aided by examples of muscle load-sharing as a function of optimization criteria including measures of position error, muscle stress and neural effort.

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