Validation of a New Dynamic Muscle Fatigue Model and DMET AnalysisReport as inadecuate




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1 IRCCyN - Institut de Recherche en Communications et en Cybernétique de Nantes 2 Laboratoire Motricité, Interactions, Performance

Abstract : Automation in industries reduced the human effort, but still there are many manual tasks in industries which lead to musculo-skeletal disorder MSD. Muscle fatigue is one of the reasons leading to MSD. The objective of this article is to experimentally validate a new dynamic muscle fatigue model taking co-contraction factor into consideration using electromyo-graphy EMG and Maximum voluntary contraction MVC data. A new model Seth-s model is developed by introducing a co-contraction factor -n- in R. Ma-s dynamic muscle fatigue model. The experimental data of ten subjects are used to analyze the muscle activities and muscle fatigue during extension-flexion 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 index decreases. The dynamic muscle fatigue model is validated using the MVC data, fatigue rate and co-contraction factor of the subjects. It has been found that with the increase in muscle fatigue, co-contraction index decreases and 90% of the subjects followed the exponential function predicted by fatigue model. The model is compared with other models on the basis of dynamic maximum endurance time DMET. The co-contraction has significant effect on the muscle fatigue model and DMET. With the introduction of co-contraction factor DMET decreases by 25.9% as compare to R. Ma-s Model.

Keywords : Muscle fatigue maximum voluntary contraction MVC muscle fatigue model co-contraction fatigue rate electromyography EMG maximum endurance time MET industrial ergonomics





Author: Deep Seth - Damien Chablat - Fouad Bennis - Sophie Sakka - Marc Jubeau - Antoine Nordez -

Source: https://hal.archives-ouvertes.fr/



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