• DocumentCode
    504253
  • Title

    Identification of wrist EMG signals using dry type electrodes

  • Author

    Oyama, Tadahiro ; Choge, Hillary ; Karungaru, Stephen ; Tsuge, Satoru ; Mitsukura, Yasue ; Fukumi, Minoru

  • Author_Institution
    Univ. of Tokushima, Tokushima, Japan
  • fYear
    2009
  • fDate
    18-21 Aug. 2009
  • Firstpage
    4433
  • Lastpage
    4436
  • Abstract
    Recently, researches of artificial arms and pointing devices using electromyogram(EMG) have been actively done. However, EMG is usually measured from a part with comparatively big muscular fibers such as arms and shoulders. Therefore, if we can recognize wrist motions using EMG which was measured from the wrist, the range of application will extend furthermore. However, when we use the wrist EMG, there are problems that the individual difference is large and its repeatability is low and so on. In this paper, we aim the construction of wrist EMG recognition system that is robust to these problems.
  • Keywords
    biomechanics; biomedical electrodes; electromyography; dry-type electrodes; wrist EMG signals; wrist motions; Arm; Electrodes; Electromyography; Feature extraction; Muscles; Neural networks; Optical fiber devices; Pattern recognition; Signal processing; Wrist; EMG; Simple-FLDA; neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    ICCAS-SICE, 2009
  • Conference_Location
    Fukuoka
  • Print_ISBN
    978-4-907764-34-0
  • Electronic_ISBN
    978-4-907764-33-3
  • Type

    conf

  • Filename
    5332982