Medical Engineering & Physics
Volume 31, Issue 5 , Pages 558-564, June 2009

Automatic detection method of muscle fiber movement as revealed by ultrasound images

  • Tasuku Miyoshi

      Affiliations

    • Shibaura Institute of Technology, 307 Fukasaku, Minuma-ku, Saitama-city, Saitama 3378570, Japan
    • Corresponding Author InformationCorresponding author at: Systems Engineering, Shibaura Institute of Technology, 307 Fukasaku, Minuma-ku, Saitama-city, Saitama 3378570, Japan. Tel.: +81 48 6889405; fax: +81 48 6875197.
    • ,
  • Tomohiko Kihara

      Affiliations

    • Okayama University of Science, 1-1 Ridaicho, Okayama-city, Okayama 7000005, Japan
    • ,
  • Hiroyuki Koyama

      Affiliations

    • Shibaura Institute of Technology, 307 Fukasaku, Minuma-ku, Saitama-city, Saitama 3378570, Japan
    • ,
  • Shin-Ichiro Yamamoto

      Affiliations

    • Shibaura Institute of Technology, 307 Fukasaku, Minuma-ku, Saitama-city, Saitama 3378570, Japan
    • ,
  • Takashi Komeda

      Affiliations

    • Shibaura Institute of Technology, 307 Fukasaku, Minuma-ku, Saitama-city, Saitama 3378570, Japan

Received 17 March 2008; received in revised form 7 November 2008; accepted 14 November 2008. published online 25 December 2008.

Abstract 

The objective of this study was to develop a method of muscle structure measurement based on the automatic analysis of muscle fibers, proximal fascias, and distal aponeurosis movements as revealed by a time-series of ultrasound images. This method was designed to detect changes in the length of muscle fiber movements, and its validity was demonstrated in a time-series of muscle movement, slow ankle dorsiflexion (10°/s), by comparison to manual measurement. The results showed that, when this method was used, the changes in the length of the muscle fiber under slow muscle movement were smaller than those in manual operations by novice individuals. However, with the proposed method, it was possible to obtain a sufficient degree of validity and reliability for the changes in the length of the muscle fiber length compared with those in manual operations, since the correlation coefficients exceeded 0.8 which was tested by the linear regression. The proposed method suggests that automation reduces the errors caused by manual operations and makes the processing of data possible in an acceptable amount of time.

Keywords: Ultrasound images, Automatic analysis, Manual operation, Muscle fiber movements

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PII: S1350-4533(08)00208-7

doi:10.1016/j.medengphy.2008.11.004

Medical Engineering & Physics
Volume 31, Issue 5 , Pages 558-564, June 2009

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