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Predicting Muscle Fatigue: A Response Surface Approximation Based On Proper Generalized Decomposition Technique

M. Sierra, J. Grasa, M. J. Muñoz, F. J. Miana-Mena, D. Gonzalez
Published 2017 · Materials Science, Medicine

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A novel technique is proposed to predict force reduction in skeletal muscle due to fatigue under the influence of electrical stimulus parameters and muscle physiological characteristics. Twelve New Zealand white rabbits were divided in four groups ($$n=3$$n=3) to obtain the active force evolution of in vitro Extensor Digitorum Longus muscles for an hour of repeated contractions under different electrical stimulation patterns. Left and right muscles were tested, and a total of 24 samples were used to construct a response surface based in the proper generalized decomposition. After the response surface development, one additional rabbit was used to check the predictive potential of the technique. This multidimensional surface takes into account not only the decay of the maximum repeated peak force, but also the shape evolution of each contraction, muscle weight, electrical input signal and stimulation protocol. This new approach of the fatigue simulation challenge allows to predict, inside the multispace surface generated, the muscle response considering other stimulation patterns, different tissue weight, etc.
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