In-vivo estimation of the human elbow joint dynamics during passive movements based on the musculo-skeletal kinematics computation

Abstract

Human upper limb joints dynamics is very important in the fields of humanoid robotics, medical robotics as well as medical research. To make human-like passive movements of the arms when walking humanoid robot arms must have similar dynamics to the human arms, even more if this arm is to be used as a prosthesis. Moreover medical diagnosis of muscle or neuro-motor diseases are based on a visual qualitative estimation of joint passive stiffness. There is a pressing need in human body dynamics characterization and especially in subject specific characterization. In this paper a solution to estimate in-vivo the passive dynamic of the arm joint is proposed. It is based on the use of the musculo-skeletal description of the human body and its kinematics computation. The linear passive joint dynamics: stiffness, viscosity and friction, is then estimated with least squares method. Acquisition of movements both designed for estimation or from medical diagnosis check-up, are achieved with motion capture studio only (no pain, no distress on subject). Experimental results for three valid subject are given