DocumentCode :
2989776
Title :
Identifying musculo-tendon parameters of human body based on the musculo-skeletal dynamics computation and Hill-Stroeve muscle model
Author :
Venture, Gentiane ; Yamane, Katsu ; Nakamura, Yoshihiko
Author_Institution :
Dept. of Mechano-Inf., Tokyo Univ.
fYear :
2005
fDate :
5-5 Dec. 2005
Firstpage :
351
Lastpage :
356
Abstract :
The goal of the works presented in this paper is to study the feasibility of the in-vivo estimation of the musculo-tendon dynamics using an original approach. Contrarily to usual literature in this field the Hill-Stroeve based model parameters are estimated, and not only some global parameters with little physiological meaning. This estimation is based on the computation of the inverse kinematics and the inverse dynamics of the human body, using a musculo-skeletal description. It also includes an optimization of the muscle force. Muscles are described by a modified and simplified Hill-type model. Parameters involved in this model are estimated in-vivo. In the preliminary works the flexion-extension of the elbow joint only is considered. Experimental set-up includes EMGs acquisition and motion capture data. Movements are chosen to limit cocontraction of antagonist muscles. Results are given for three of four muscles involved in the joint movements. Such results are very important for medical applications in rehabilitation, sport science, study of muscle diseases
Keywords :
biomechanics; muscle; robot dynamics; robot kinematics; Hill-Stroeve muscle model; inverse dynamics; inverse kinematics; invivo estimation; motion capture data; musculo-skeletal dynamics computation; musculo-tendon parameters; Biological system modeling; Biomedical equipment; Elbow; Electromyography; Humans; Joints; Kinematics; Medical services; Muscles; Parameter estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Humanoid Robots, 2005 5th IEEE-RAS International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
0-7803-9320-1
Type :
conf
DOI :
10.1109/ICHR.2005.1573592
Filename :
1573592
Link To Document :
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