• DocumentCode
    3088884
  • Title

    Myoelectric based virtual joystick applied to electric powered wheelchair

  • Author

    Oskoei, Mohammadreza Asghari ; Hu, Huosheng

  • Author_Institution
    Dept. of Comput. & Electron. Syst., Univ. of Essex, Colchester
  • fYear
    2008
  • fDate
    22-26 Sept. 2008
  • Firstpage
    2374
  • Lastpage
    2379
  • Abstract
    This paper proposes a myoelectric-based virtual joystick to manipulate an electric powered wheelchair for people with severe motor disabilities. It is built on pattern recognition-based myoelectric control that discriminates muscular activities using forearmpsilas surface myoelectric signals. The core of the system is a support vector machine based classifier that classifies signal time domain features. Online training scheme is applied to cope with gradual changes in myoelectric signal patterns. Two indexes, contineousness and entropy, were used to update training data set in real time operation. The results confirm that the proposed myoelectric-based joystick is a reliable alternative for traditional joysticks and its performance is fairly acceptable.
  • Keywords
    electromyography; handicapped aids; interactive devices; pattern classification; support vector machines; wheelchairs; electric powered wheelchair; forearm surface myoelectric signal; motor disability; muscular activity; myoelectric based virtual joystick; myoelectric signal pattern; online training scheme; pattern recognition-based myoelectric control; support vector machine based classifier; Accuracy; Entropy; Indexes; Support vector machines; Training; Training data; Wheelchairs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on
  • Conference_Location
    Nice
  • Print_ISBN
    978-1-4244-2057-5
  • Type

    conf

  • DOI
    10.1109/IROS.2008.4650664
  • Filename
    4650664