A nonlinear tracking method of computing net joint torques for human movement

Abstract

Determining individual muscles forces from human performance has greatly depended on the quality of inverse dynamics solutions, as muscle force decomposition remains the only feasible approach for determining muscle forces non-invasively in human movement. However, legitimate questions about the accuracy of inverse dynamics arise, with resultant torques/forces failing to drive a forward model through the observations from which they were derived. While optimization of forward dynamics to match experimental data is considered more accurate, the simplicity and low computational costs of inverse methods are favored over the large computing requirements of optimization. In this paper, an evolution in the inverse methods for computing accurate and reliable torques is presented, whereby the relative speed of inverse dynamics is combined with the desired accuracy of forward dynamics. This method is based on developing a nonlinear tracker that determines the net muscle torques which accurately follow clinically observed kinematics and ground reaction forces. The results show that the method is robust and can produce accurate estimates of the joint torques during movement. The method outlined here is a necessary first step to solving the muscle force indeterminancy problem more efficiently.