Identification of human musculo-tendon subject specific dynamics using musculo-skeletal computations and non linear least square

The human body dynamics is very complex because of the number of degrees of freedom and of the number of muscles. Moreover the behavior of muscles is non-linear and subject specific. This paper presents an original method to estimate the subject specific dynamic parameters of the human muscles. A dynamic model of muscle, commonly used by the biomechanics community, is first presented. Then the force-activity-length-velocity relation is given. An application with four muscles, to the flexion/extension of the elbow joint is proposed. The human arm dynamics is analyzed in a motion capture studio for specific movements that excite the muscle dynamics. The acquisition of movements allows to compute the inverse kinematics and the inverse dynamics using a musculo-skeletal model of the human body, and finally the muscle force is estimated (input of the dynamic model of the muscle). The activity (also input of the dynamic model of the muscle) is measured using electromyography (EMGs) for the superficial muscles. The subject specific parameters of those muscles are then estimated by the non-linear least square method with Newton-Gauss algorithm. Experimental results obtain for valid subject are given