Abstract
The surface EMG signal is an electrophysiological signal generated by muscle contraction and collected by placing electrodes on the skin surface, which contains rich information about muscle function and state. The current exoskeleton design also urgently needs to evaluate the muscle contribution to assist joint or part movement, and this result will directly affect the theoretical design of the exoskeleton. From this perspective, in this paper, we measured the surface EMG data during squatting for 10 test subjects, and set up a control group and an test group, with each control group doing 10 continuous squats and each test group doing 10 continuous squats with a hand weight of 10 kg. In this paper, 60 sets of surface EMG data of squatting movements of 10 test subjects were analyzed, and the contribution of 12 different parts of muscles was evaluated based on covariance matrix, and it was obtained that rectus femoris contributed more than 15% of the 12 muscles without weight-bearing, but the contribution of rectus femoris decreased by 50% under weight-bearing condition, and the contribution of medial femoris and biceps femoris increased significantly to more than 15% of the overall.
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Wang, Z., Guan, X., Li, Z., Zheng, B., Li, H., Bai, Y. (2022). Surface Electromyography-Based Assessment of Muscle Contribution in Squatting Movements. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13457. Springer, Cham. https://doi.org/10.1007/978-3-031-13835-5_67
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DOI: https://doi.org/10.1007/978-3-031-13835-5_67
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