Abstract
The objective of this study is to try solving the muscle redundancy problem by artificial neural network and discuss about the strategy to exert the muscles. We created two-dimensional model of an ergometer and a lower limb with one degree of freedom including six muscles acting on hip and knee joints. The training data were corrected with random postures and muscle exertions. The system decided the muscle exertions inputting the body posture and the force vector to be acted on a crank. The external force was applied in order to observe how the antagonists work. As a result, the average muscle exertion was a half of the maximum. However, adding the subject to reduce the sum of muscle exertions, it changed and output the physiological results. The antagonists exerted when the external forces were large.
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Fukunaga, M. (2021). How the Artificial Neural Network Solves the Muscle Redundancy Problem During Pedaling Motion?. In: Cassenti, D., Scataglini, S., Rajulu, S., Wright, J. (eds) Advances in Simulation and Digital Human Modeling. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1206. Springer, Cham. https://doi.org/10.1007/978-3-030-51064-0_40
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DOI: https://doi.org/10.1007/978-3-030-51064-0_40
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