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Journal Articles International Journal of Virtual Reality Year : 2016

Validation of a New Dynamic Muscle Fatigue Model and DMET Analysis


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.
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hal-01420684 , version 1 (20-12-2016)


  • HAL Id : hal-01420684 , version 1


Deep Seth, Damien Chablat, Bennis Fouad, Sophie Sakka, Marc Jubeau, et al.. Validation of a New Dynamic Muscle Fatigue Model and DMET Analysis. International Journal of Virtual Reality, 2016, The International Journal of Virtual Reality, 2016 (16). ⟨hal-01420684⟩
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