• DocumentCode
    178207
  • Title

    Fingertip force estimation from forearm muscle electrical activity

  • Author

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

  • Author_Institution
    Worcester Polytech. Inst., Worcester, MA, USA
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    2069
  • Lastpage
    2073
  • Abstract
    Existing commercial hand prostheses can be controlled from the electrical activity (electromyogram or EMG) of remnant muscle tissue within the forearm, but are limited in function to one degree of freedom of proportional control. In a pilot study (N=3 subjects), we used least squares estimation to identify a model between forearm electrical activity recorded by high-resolution (64 channel) electrode arrays (applied over the flexor and, separately, extensor muscles of the forearm) to force in the four fingertips. Average errors ranged from 4.21 to 10.20 %MVCF (flexion maximum voluntary contraction), depending on the muscle contraction task performed, number of EMG electrodes in the model and the electrode montage selected. Results suggest that, at least for intact subjects, 2-4 degrees of freedom of proportional control are available from the EMG signals of the forearm.
  • Keywords
    biomedical electrodes; electromyography; least squares approximations; medical signal processing; prosthetics; EMG; MVCF; electrode montage; electromyogram; fingertip force estimation; flexion maximum voluntary contraction; flexor; forearm extensor muscles; forearm muscle electrical activity; hand prostheses; high-resolution electrode arrays; least squares estimation; muscle contraction task; remnant muscle tissue; Electrodes; Electromyography; Force; Muscles; Spatial filters; Thumb; EMG signal processing; EMG-force; biomedical signal processing; electromyography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6853963
  • Filename
    6853963