14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract

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Paper FrA6.3

Venture, Gentiane (Univ. of Tokyo)

Application of Non-Linear Least Square Method to Estimate the Muscle Dynamics of the Elbow Joint

Scheduled for presentation during the Regular Session "Identification in Biological Systems" (FrA6), Friday, March 31, 2006, 11:10−11:30, Newcastle Room

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 16, 2018

Keywords Biological Systems, Nonlinear System Identification, Multivariable System Identification

Abstract

This paper presents an original use of the non-linear least-squares method applied to the muscle dynamics of the human body. 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. A dynamic model of muscle, commonly used by the biomechanics community, which is presented, gives a relation between muscle force, activity, length and velocity. An application to the flexion/extension of the joint elbow using four muscles is then proposed. The dynamic parameters of those four muscles are estimated experimentally by the non-linear least square method. The activity (input of the dynamic model of the muscle) is measured using electromyography. The human arm dynamics is analyzed in a motion capture studio which acquisition of movements allows to compute the inverse kinematics and the inverse dynamics. Finally the muscle force is estimated (input of the dynamic model of the muscle).