• DocumentCode
    471597
  • Title

    Vibromyographic Quantification of Voluntary Isometric Contractile Force in the Brachioradialis

  • Author

    Cole, Jason P. ; Madhavan, Guruprasad ; McLeod, Kenneth J.

  • Author_Institution
    Dept. of Bioeng., State Univ. of New York, Binghamton, NY
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 3 2006
  • Firstpage
    1708
  • Lastpage
    1710
  • Abstract
    This study investigated the ability of vibromyography (VMG) to accurately represent voluntary forearm muscle contractile force during attempted-isometric contraction of the brachioradialis. VMG signals were collected from the brachioradialis of healthy adult men (mean age, 26.6plusmn9.8 years, N=24) during attempted-isometric contraction over a force range of 4.45 N to maximum sustained load. The VMG signals were decomposed using wavelet packet analysis techniques, and the corresponding wavelet packets were utilized in a multiple regression model for parameter reduction and identification of signal components which best correlated to muscle force. It was observed that just two wavelet components were sufficient to accurately predict muscle force (R 2=0.984, P<0.0001). The signal force relationship observed is monotonic, though quadratic in form. More importantly, the wavelet data was able to predict absolute force output of the brachioradialis without normalization or prior knowledge of a subject´s maximum voluntary force. These data show that VMG recordings are capable of providing a monotonic relationship between VMG signal and muscle force. Moreover, in contrast to EMG technology which can only provide relative force levels, VMG appears to be capable of reporting absolute force levels, an observation which is expected to lead to numerous applications in medicine and rehabilitation
  • Keywords
    biomechanics; biomedical measurement; electromyography; force measurement; regression analysis; wavelet transforms; attempted-isometric contraction; brachioradialis; electromyography; healthy adult men; mechanomyography; multiple regression model; muscle force measurement; parameter identification; parameter reduction; vibromyography; voluntary forearm muscle contractile force; wavelet packet analysis techniques; Bone diseases; Elbow; Electromyography; Force measurement; Muscles; Protocols; Signal processing; Skin; Wavelet analysis; Wavelet packets; Electromyography; Mechanomyography; Muscle Force Measurement; Vibromyography; Wavelet Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
  • Conference_Location
    New York, NY
  • ISSN
    1557-170X
  • Print_ISBN
    1-4244-0032-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2006.260152
  • Filename
    4462101