A new method for muscle fatigue assessment: Online model identification techniques

Maria Papaiordanidou, Mitsuhiro Hayashibe, Alain Varray, Charles Fattal, David Guiraud

Research output: Contribution to journalArticlepeer-review

Abstract

Introduction: The purpose of this study was to propose a method that allows extraction of the current muscle state under electrically induced fatigue. Methods: The triceps surae muscle of 5 subjects paralyzed by spinal cord injury was fatigued by intermittent electrical stimulation (5 × 5 trains at 30 Hz). Classical fatigue indices representing muscle contractile properties [peak twitch (Pt) and half-relaxation time (HRT)] were assessed before and after each 5-train series and were used to identify 2 relevant parameters (Fm, Ur) of a previously developed mathematical model using the Sigma-Point Kalman Filter. Results: Pt declined significantly during the protocol, whereas HRT remained unchanged. Identification of the model parameters with experimental data yielded a model-based fatigue assessment that gave a more stable evaluation of fatigue than classical parameters. Conclusions: This work reinforces clinical research by providing a tool that clinicians can use to monitor fatigue development during stimulation.

Original languageEnglish
Pages (from-to)556-563
Number of pages8
JournalMuscle and Nerve
Volume50
Issue number4
DOIs
Publication statusPublished - 2014 Oct 1
Externally publishedYes

Keywords

  • Contractile apparatus
  • Identification method
  • Muscle model
  • Paraplegia
  • Sigma-Point Kalman Filter

ASJC Scopus subject areas

  • Physiology
  • Clinical Neurology
  • Cellular and Molecular Neuroscience
  • Physiology (medical)

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