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Designing advanced controllers for motor neural prosthesis applications requires appropriate models for electrically stimulated muscle. A nonlinear nonisometric muscle model based on a Hill-type structure is presented. Estimation algorithms were derived to parameterize the passive force-length, the passive force-velocity, the active force-length, and the active force-velocity properties, the isometric recruitment curve, and the linear contraction dynamics of the model. All parameters were based on experimental measurements rather than on values taken from the literature. The estimation methods were validated experimentally using isolated hind-limb muscles in two acute animal model preparations. The results demonstrated that the parameterized model is capable of predicting force output with reasonable accuracy for a wide range of simultaneously varying kinematic and stimulation inputs.
Date of Publication: March 1994