• DocumentCode
    3256151
  • Title

    Pattern recognition of electromyography applied to Exoskeleton Robot

  • Author

    Wang, Yang ; Zhang, Xiaodong ; Zhao, Jianping ; He, Chen

  • Author_Institution
    Sch. of Engine & Energy, Northwestern Polytech. Univ., Xi´´an, China
  • Volume
    8
  • fYear
    2010
  • fDate
    16-18 Oct. 2010
  • Firstpage
    3802
  • Lastpage
    3805
  • Abstract
    Exoskeleton Robot is a robotic-assisted human-machine system, which can provide power to assist the movement of people. This paper aims to find a method of EMG pattern recognition used in Exoskeleton Robot. To the beginning, the EMG power spectrum ratio (PSR) is calculated as the EMG eigenvalue. Then the minimum error-based Bayes decision rule is used to determine the movement intention of human, implemented in Matlab. The research result shows that the power spectrum density rate and the minimum error-based Bayesian decision theory can recognize the EMG on the movement intention of lower extremity exoskeleton with the advantages of easy reality and fast compute by Matlab.
  • Keywords
    Bayes methods; decision theory; electromyography; feature extraction; human-robot interaction; medical robotics; robot vision; EMG pattern recognition; Matlab; electromyography; exoskeleton robot; minimum error based Bayesian decision theory; power spectrum ratio; robotic assisted human machine system; Bayesian methods; Electromyography; Exoskeletons; Legged locomotion; Muscles; Pattern recognition; EMG; exoskeletal robot; feature extraction; pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2010 3rd International Congress on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4244-6513-2
  • Type

    conf

  • DOI
    10.1109/CISP.2010.5646759
  • Filename
    5646759