A new method for muscle fatigue assessment: Online model identification techniques - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Journal Articles Muscle & Nerve Year : 2014

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

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 (5x5 trains at 30Hz). 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 significantly declined during the protocol, while 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. Discussion: This work reinforces clinical research by providing a tool that clinicians can use to monitor fatigue development during stimulation.

Dates and versions

lirmm-00952416 , version 1 (26-02-2014)

Identifiers

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Maria Papaiordanidou, Mitsuhiro Hayashibe, Alain Varray, Charles Fattal, David Guiraud. A new method for muscle fatigue assessment: Online model identification techniques. Muscle & Nerve, 2014, 50 (4), pp.556-563. ⟨10.1002/mus.24190⟩. ⟨lirmm-00952416⟩
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