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

Maria Papaiordanidou 1, 2 Mitsuhiro Hayashibe 1 Alain Varray 2 Charles Fattal 3 David Guiraud 1, *
* Corresponding author
1 DEMAR - Artificial movement and gait restoration
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
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.
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Journal articles
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00952416
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Submitted on : Wednesday, February 26, 2014 - 5:06:49 PM
Last modification on : Thursday, February 7, 2019 - 5:02:28 PM

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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 and Nerve, Wiley, 2014, 50 (4), pp.556-563. ⟨10.1002/mus.24190⟩. ⟨lirmm-00952416⟩

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