• DocumentCode
    2613963
  • Title

    A Prediction Method of Muscle Force Using sEMG

  • Author

    Li, Gang ; Chen, Haifeng ; Lee, Jungtae

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Pusan Nat. Univ., Busan, South Korea
  • fYear
    2009
  • fDate
    17-20 April 2009
  • Firstpage
    501
  • Lastpage
    505
  • Abstract
    Surface electromyography (sEMG) technology is used to record and display the electrical activities of human muscles, by which researchers are able to make a muscle force evaluation. In this study, in order to accurately feedback the information about athletes´ forearm force training, the Maximum Voluntary Contraction (MVC) is proved as the indicator of maximum forearm muscle force by developing a winner prediction method of arm wrestling game. Experiment results based on healthy 12 volunteers´ (all males, average age is 25 plusmn 3) are reported in this paper. The results show that the prediction method can be accurately performed so as to estimate who is the winner.
  • Keywords
    bioelectric phenomena; biomedical measurement; electromyography; force measurement; medical signal processing; sport; arm wrestling game; athlete; electrical activities; forearm force training; human muscles; maximum voluntary contraction; muscle force evaluation; prediction method; surface electromyography; Computer science; Electrodes; Electromyography; Force control; Force feedback; Force measurement; Muscles; Prediction methods; Signal processing; Springs; MVC; arm wrestling; athletes´ force training; sEMG signal processing; surface electromyography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology - Spring Conference, 2009. IACSITSC '09. International Association of
  • Conference_Location
    Singapore
  • Print_ISBN
    978-0-7695-3653-8
  • Type

    conf

  • DOI
    10.1109/IACSIT-SC.2009.11
  • Filename
    5169403