• DocumentCode
    2184787
  • Title

    Dynamic modeling of spinal electromyographic activity during various conditions

  • Author

    Jonckheere, E.A. ; Lohsoonthorn, P. ; Boone, R.

  • Author_Institution
    Dept. of Electr. Eng.-Syst., Univ. of Southern California, Los Angeles, CA, USA
  • Volume
    1
  • fYear
    2003
  • fDate
    4-6 June 2003
  • Firstpage
    465
  • Abstract
    The surface electromyographic (sEMG) signals recorded along the spine during a rocking motion created by feedback coupling between the motion of the spine and the efferent nerve fibers at the dural attachment points are giving various linear dynamical models of the ARIMA type. The most significant dynamical phenomenon is the nonlinear switching among the various linear models. The switchings represent transitions among qualitatively different modes of the motion of the spine, referred to as Levels 1, 2, 3. Statistical analysis reveals a definite relationship between the qualitatively assessed levels and the various quantitatively relevant models. Finally, it is shown that the higher the level of care, the more reliable the model, that is, the better the model is able to predict the motion as specified by the sEMG signal.
  • Keywords
    autoregressive moving average processes; electromyography; feedback; neurophysiology; physiological models; statistical analysis; ARIMA type; EMG signal; dynamic modeling; efferent nerve fibers; feedback coupling; linear dynamical models; nonlinear switching; qualitatively assessed levels; spinal electromyographic activity; spine motion; statistical analysis; Central nervous system; Diseases; Ligaments; Medical services; Nerve fibers; Pathology; Predictive models; Spinal cord; Spine; Strips;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2003. Proceedings of the 2003
  • ISSN
    0743-1619
  • Print_ISBN
    0-7803-7896-2
  • Type

    conf

  • DOI
    10.1109/ACC.2003.1239052
  • Filename
    1239052