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The implementation of the 3CC muscle fatigue model into CEINMS

Gabriël, Gaston Ramon (2023) The implementation of the 3CC muscle fatigue model into CEINMS.

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Abstract:Muscle injuries are prevalent in various fields, including sports and manual labour. Muscle fatigue has been recognized as one of its contributing factors. Modern fatigue models use empirical or theoretical approaches but lack personalized estimates of muscle and joint dynamics. The Calibrated EMG-Informed neuromusculoskeletal model (CEINMS) enables these estimates but does not consider fatigue dynamics. Evidently, a model that captures central and peripheral fatigue, and can be personalized is needed. This study proposed a novel approach of the combination of the three-compartment fatigue model (3CC) with CEINMS, called CEINMS+. Two datasets were conducted. One, the ankle study, did not show fatigue. Hence, we proposed repetition of heel raises till exhaustion to induce fatigue. The other, lifting study, did show fatigue. Results proved CEINMS+’ validity: RMSE between gold standard Inverse Dynamics (ID) and CEINMS+ decreased w.r.t. CEINMS (range: 0-1.01 Nm/kg) but correlation coefficients remained unchanged (range: 0.62-0.97). Significant differences (p<0.01) in peak torque estimates between CEINMS and ID were found (range: 0.83-1.19 Nm/kg), but not between CEINMS+ and ID (range: 0.09-0.44 Nm/kg). For future studies, we proposed real-time analysis of joint dynamics, the improvement on motor unit recruitment modelling, and the addition of muscle synergies. Ultimately, CEINMS+ proved a valid approach to help understand one of muscle injuries’ underlying mechanisms.
Item Type:Essay (Master)
Faculty:ET: Engineering Technology
Subject:42 biology, 52 mechanical engineering
Programme:Biomedical Engineering MSc (66226)
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