MUSCLE JOINT MODELS INCORPORATING ACTIVATION DYNAMICS, MOMENT ANGLE, AND MOMENT VELOCITY PROPERTIES

Muscle input/output models incorporating activation dynamics, moment-a ngle, and moment-velocity factors are commonly used to predict the mom ent produced by muscle during nonisometric contractions; the three fac tors are generally assumed to be independent. We examined the ability of models with independent factors, as well as models with coupled fac tors, to fit input/output data measured during simultaneous modulation of the fraction of muscle stimulated (recruitment) and joint angle in puts. The models were evaluated in stimulated cat soleus muscles produ cing ankle extension moment, with regard to their potential applicatio ns in neuroprostheses with either fixed parameters or parameter adapta tion. Both uncoupled and coupled models predicted the output moment we ll for random angle perturbation sizes ranging from 10 degrees to 30 d egrees. For the uncoupled model, the best parameter values depended on the range of perturbations and the mean angle. Introducing coupling b etween activation and velocity in the model reduced this parameter sen sitivity; one set of model parameter values fit the data for all pertu rbation sizes and also fit the data under isometric or constant stimul ation conditions. Thus, the coupled model would be the most appropriat e for applications requiring fixed parameter values. In contrast, with continuous parameter adaptation, errors due to changing test conditio ns decreased more quickly for the uncoupled model, suggesting that it would perform well in adaptive control of neuroprostheses.