• DocumentCode
    793898
  • Title

    A predictive fatigue model. I. Predicting the effect of stimulation frequency and pattern on fatigue

  • Author

    Ding, Jun ; Wexler, Anthony S. ; Binder-Macleod, Stuart A.

  • Author_Institution
    Interdisciplinary Graduate Program in Biomech. & Movement Sci., Delaware Univ., Newark, DE, USA
  • Volume
    10
  • Issue
    1
  • fYear
    2002
  • fDate
    3/1/2002 12:00:00 AM
  • Firstpage
    48
  • Lastpage
    58
  • Abstract
    Previously we developed a mathematical force- and fatigue-model system that could predict fatigue produced by a wide range of frequencies and pulse patterns. However, the models tended to overestimate the forces produced by higher frequency trains. This paper presents modifications to our previously developed force- and fatigue-model system to improve the accuracy in predicting forces during repetitive activation of human skeletal muscle. By comparing the predictions produced by the modified force and fatigue models to those by our previous models, the modification appears to be successful. The current force- and fatigue-model system accounts for about 93% variance in experimental data produced by fatigue protocols consisting of trains with a wide range of frequencies and pulse patterns. In addition, the present models successfully predict the effect of stimulation frequency and pulse pattern on muscle fatigue. The success of our current force- and fatigue-model system suggests its potential use in helping to identify the optimal activation pattern to use during the clinical application of functional electrical stimulation.
  • Keywords
    biomechanics; neuromuscular stimulation; physiological models; clinical application; experimental data variance; higher frequency trains; human skeletal muscle; mathematical model system; optimal activation pattern; pulse patterns; repetitive activation; stimulation frequency; stimulation pattern; Biomechanics; Electrical stimulation; Fatigue; Frequency; Humans; Muscles; Neuromuscular stimulation; Predictive models; Protocols; Testing; Algorithms; Electric Stimulation; Humans; Isometric Contraction; Models, Biological; Muscle Fatigue; Muscle, Skeletal; Reproducibility of Results; Sensitivity and Specificity; Stress, Mechanical; Thigh;
  • fLanguage
    English
  • Journal_Title
    Neural Systems and Rehabilitation Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1534-4320
  • Type

    jour

  • DOI
    10.1109/TNSRE.2002.1021586
  • Filename
    1021586