PREDICTION OF MUSCLE FORCES USING STATIC OPTIMIZATION FOR DIFFERENT CONTRACTILE CONDITIONS
Tarih
2013Yazar
Herzog, Walter
Arslan, YUNUS ZİYA
Jinha, Azim
Kaya, Motoshi
Üst veri
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In this study, we introduced a novel cost function for the prediction of individual muscle forces for a one degree-of-freedom musculoskeletal system. Unlike previous models, the new approach incorporates the instantaneous contractile conditions represented by the force-length and force-velocity relationships and accounts for physiological properties such as fiber type distribution and physiological cross-sectional area (PCSA) in the cost function. Using this cost function, it is possible to predict experimentally observed features of force-sharing among synergistic muscles that cannot be predicted using the classical approaches. Specifically, the new approach allows for predictions of force-sharing loops of agonistic muscles in one degree-of-freedom systems and for simultaneous increases in force in one muscle and decreases in a corresponding agonist. We concluded that the incorporation of the contractile conditions in the weighting of cost functions provides a natural way to incorporate observed force-sharing features in synergistic muscles that have eluded satisfactory description.
Koleksiyonlar
- Makale [92796]