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lirmm-00637754, version 1

Muscle Strength and Mass Distribution Identification Toward Subject-Specific Musculoskeletal Modeling

Mitsuhiro Hayashibe (Author to contact preferably, http://www.lirmm.fr/~hayashibe) 12, Gentiane Venture 3, Ko Ayusawa 4, Yoshihiko Nakamura 4

IROS'11: IEEE/RSJ International Conference on Intelligent Robots and Systems 3701-3707

  • 1:  DEMAR (INRIA Sophia Antipolis)
  • http://www.lirmm.fr/DEMAR/
    INRIA – CNRS : UMR5506 – Université Montpellier II - Sciences et techniques – Université Montpellier I LIRMM 161 rue Ada 34392 Montpellier Cedex 5 France France
  • 2:  Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM)
  • http://www.lirmm.fr
    CNRS : UMR5506 – Université Montpellier II - Sciences et techniques CC 477, 161 rue Ada, 34095 Montpellier Cedex 5 France
  • 3:  Tokyo University of Agriculture and Technology

  • Tokyo University of Agriculture and Technology Japan
  • 4:  Nakamura Laboratory (Department of Mechano-Informatics)
  • http://www.ynl.t.u-tokyo.ac.jp/
    University of Tokyo Nakamura & Yamane Laboratory Department of Mechano-Informatics, Graduate School of Information Science and Technology, The University of Tokyo. 7-3-1- Hongo, Bunkyo-ku Tokyo 113-8656 Japan

Bibliographic reference

  • Type of document: Peer-reviewed conferences/proceedings
  • Title: Muscle Strength and Mass Distribution Identification Toward Subject-Specific Musculoskeletal Modeling
  • Abstract: In current biomechanics approach, the assumptions are commonly used in body-segment parameters and muscle strength parameters due to the difficulty in accessing those subject-specific values. Especially in the rehabilitation and sports science where each subject can easily have quite different anthropometry and muscle condition due to disease, age or training history, it would be important to identify those parameters to take benefits correctly from the recent advances in computational musculoskeletal modeling. In this paper, Mass Distribution Identification to improve the joint torque estimation and Muscle Strength Identification to improve the muscle force estimation were performed combined with previously proposed methods in muscle tension optimization. This first result highlights that the reliable muscle force estimation could be extracted after these identifications. The proposed framework toward subject-specific musculoskeletal modeling would contribute to a patient-oriented computational rehabilitation.
  • Subject:
    Life Sciences/Bioengineering
    Computer Science/Modeling and Simulation
  • Fulltext language: English
  • Conference title: IROS'11: IEEE/RSJ International Conference on Intelligent Robots and Systems
  • Audience: international
  • Type: non spécifié
  • Publication date: 2011-09-26
  • Page: 3701-3707
  • Conference location: San Francisco
  • Country: United States

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  • lirmm-00637754, version 1
  • oai:hal-lirmm.ccsd.cnrs.fr:lirmm-00637754
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  • Submitted on: Wednesday, 2 November 2011 18:15:52
  • Updated on: Friday, 4 November 2011 11:36:03