Experimental Validation of a New Dynamic Muscle Fatigue Model

  • Deep Seth
  • Damien ChablatEmail author
  • Sophie Sakka
  • Fouad Bennis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9745)


Muscle fatigue is considered as one of the major risk factor causing Musculo-Skeletal Disorder (MSD). To avoid MSD the study of muscle fatigue is very important. For the study of muscle fatigue a new model is developed by modifying the Ruina Ma’s dynamic muscle fatigue model and introducing the muscle co-contraction factor ‘n’ in this model. The aim of this paper is to experimentally validate a dynamic muscle fatigue model using Electromyography (EMG) and Maximum Voluntary Contraction (MVC) data. The data of ten subjects are used to analyze the muscle activities and muscle fatigue during the extension-flexion (push-pull) motion of the arm on a constant absolute value of the external load. The findings for co-contraction factor shows that the fatigue increases when co-contraction area decreases. The dynamic muscle fatigue model is validated using the MVC data, fatigue rate and co-contraction factor of the subjects.


Muscle fatigue Maximum Voluntary Contraction (MVC) Muscle fatigue model Co-contraction Fatigue rate Electromyography (EMG) 



The project is funded by the European Commission under the ‘Erasmus Mundus Heritage Program’, jointly coordinated by Ecole Centrale de Nantes, France and Indian institute of Technology Madras, India. The Experiments was performed in STAPS, University of Nantes, France. We are also thankful to Antoine Nordez and Marc Jubeau from UFR STAPS, France for assistance in preparing and conducting the experiments.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Deep Seth
    • 1
  • Damien Chablat
    • 1
    Email author
  • Sophie Sakka
    • 1
  • Fouad Bennis
    • 1
  1. 1.IRCCyN, Ecole Centrale de NantesNantesFrance

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