• DocumentCode
    2107956
  • Title

    Prior estimation of motion using recursive perceptron with sEMG: A case of wrist angle

  • Author

    Kuroda, Yoshihiro ; Tanaka, T. ; Imura, M. ; Oshiro, O.

  • Author_Institution
    Grad. Sch. of Eng. Sci., Osaka Univ., Toyonaka, Japan
  • fYear
    2012
  • fDate
    Aug. 28 2012-Sept. 1 2012
  • Firstpage
    5270
  • Lastpage
    5273
  • Abstract
    Muscle activity is followed by myoelectric potentials. Prior estimation of motion by surface electromyography can be utilized to assist the physically impaired people as well as surgeon. In this paper, we proposed a real-time method for the prior estimation of motion from surface electromyography, especially in the case of wrist angle. The method was based on the recursive processing of multi-layer perceptron, which is trained quickly. A single layer perceptron calculates quasi tensional force of muscles from surface electromyography. A three-layer perceptron calculates the wrist´s change in angle. In order to estimate a variety of motions properly, the perceptron was designed to estimate motion in a short time period, e.g. 1ms. Recursive processing enables the method to estimate motion in the target time period, e.g. 50ms. The results of the experiments showed statistical significance for the precedence of estimated angle to the measured one.
  • Keywords
    electromyography; medical signal processing; motion estimation; multilayer perceptrons; recursive estimation; multilayer perceptron; muscle activity; myoelectric potentials; physically impaired people; prior motion estimation; quasitensional force; real-time method; recursive perceptron; sEMG; single layer perceptron; surface electromyography; surgeon; three-layer perceptron; time 1 ms; time 50 ms; wrist angle; Electrodes; Equations; Estimation; Force; Muscles; Training; Wrist; Electromyography; Humans; Wrist;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4119-8
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/EMBC.2012.6347183
  • Filename
    6347183