• DocumentCode
    3251202
  • Title

    EMG-force estimation for multiple fingers

  • Author

    Pu Liu ; Brown, D. Richard ; Clancy, Edward A. ; Martel, Francois ; Rancourt, Denis

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Worcester Polytech. Inst., Worcester, MA, USA
  • fYear
    2013
  • fDate
    7-7 Dec. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Electromyogram (EMG) activity from the extensor and flexor muscles of the forearm was sensed with high-density surface electrode arrays and related to the force produced at the four fingertips during constant-posture, slowly force-varying contractions from three healthy subjects. Various electrode montages (spatial filters) and number of electrodes used in the system identification were studied. Average errors were small, ranging from 4.21 to 8.10 %MVCF (flexion maximum voluntary contraction), with errors trending lower when more EMG channels were used and when a monopolar electrode montage was selected. Results are supportive that multiple degrees of freedom of proportional control information are available from the surface EMG of the forearm, at least in intact subjects. Applications for future study include the control of prosthetic upper limb devices in amputees.
  • Keywords
    biomedical electrodes; electromyography; medical signal processing; spatial filters; EMG channels; EMG-force estimation; amputees; constant posture; electromyogram activity; extensor muscles; fingertips; flexion maximum voluntary contraction; flexor muscles; force-varying contractions; forearm; high-density surface electrode arrays; monopolar electrode montage; multiple fingers; proportional control information; prosthetic upper limb devices; spatial filters; surface EMG; system identification; Accuracy; Electrodes; Electromyography; Force; MONOS devices; Muscles; Training; Biological system modeling; EMG signal processing; biomedical signal processing; electromyography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing in Medicine and Biology Symposium (SPMB), 2013 IEEE
  • Conference_Location
    Brooklyn, NY
  • Type

    conf

  • DOI
    10.1109/SPMB.2013.6736772
  • Filename
    6736772