Inverse dynamics method using optimization techniques for the estimation of muscles forces involved in the elbow motion

The goal of this study is the proposition of an inverse dynamics method using an optimization technique in order to obtain muscles from motion capture data. First, we apply an inverse kinematics algorithm to obtain joint angles from markers positions; next we compute an inverse dynamics algorithm to obtain joint torques with a generic dynamical model of human arm designed by using Matlab-Simulink Simmechanics. Those torques are used in an optimization algorithm under non-linear constraints in order to compute muscle forces. The main part of the article presents the contributions of these constraints to build an adequate cost function. We propose to improve the method with the addition of a unilateral constraint that deals with the co-contraction of the muscle. We discuss results that emphasize the interest of taking the co-contraction into account by presenting a compared analysis for an extension of the elbow. Then we focus on a solution based on interpolation into a pre-computed database. This proposition aims at improving the model to meet the real-time constraint imposed for use in virtual reality applications.

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