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

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

Research output: Contribution to journalArticle

44 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)48-58
Number of pages11
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume10
Issue number1
DOIs
StatePublished - 2002
Externally publishedYes

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Keywords

  • Functional electrical stimulation (FES)
  • Muscle fatigue
  • Muscle model

ASJC Scopus subject areas

  • Rehabilitation
  • Biophysics
  • Bioengineering
  • Health Professions(all)

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