The Development of 4D Muscle Model for 4D Quantitative Movement Analysis

DOI
  • Yamasaki Kenichi
    Graduate School of Science & Engineering, Waseda University
  • Suzuki Naoki
    Institute for High Dimensional Medical Imaging, Jikei University School of Medicine
  • Hattori Asaki
    Institute for High Dimensional Medical Imaging, Jikei University School of Medicine
  • Takatsu Akihiro
    Institute for High Dimensional Medical Imaging, Jikei University School of Medicine Deptartment of Forensic Medicine, Jikei University School of Medlcine
  • Uchiyama Akihiko
    Graduate School of Science & Engineering, Waseda University

Bibliographic Information

Other Title
  • 運動機能の四次元的解析を目的とした骨格筋モデルの開発

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Description

Until recently, we have only inferred the movement of each skeletal muscle from electromyogram measurements (EMG), anatomical information, and observations of the human body surface. However, under the present circumstances it is problematic to comprehend the connection and interaction between the human skeleton and skeletal muscles or between human skeletal muscles themselves. Thus we aimed to develop a method to quantitatively visualize these interactions in space and time sequential domains by utilizing computer graphic techniques. First, each human skeleton and muscle model was reconstructed from MRI data sets. Second, coordinates derived from a mesh framework of a muscle were converted into algorithm. This algorithm reduced all coordinates of the muscle framework while maintaining the original muscle shape. Afterwards, we were able to construct a realistic skeletal muscle model. This muscle model can contract or extend while avoiding the bone or adjacent skeletal muscle by taking physical interference into account. We also made a series of skeletal muscle models for each bone. As a result, we could observe the activity and contribution of each muscle in bone movement. In the future, by applying this system we will be able to monitor the movements of people with physical disorders.

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Details 詳細情報について

  • CRID
    1390282680367550464
  • NII Article ID
    130004256814
  • DOI
    10.5759/jscas1999.2.22
  • ISSN
    18845770
    13349486
    13449486
  • Data Source
    • JaLC
    • Crossref
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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