Abstract
In this paper, a surface Electromyography (sEMG)-based compliant rehabilitation training method for the end traction upper limb rehabilitation robot is proposed. The sEMG signal of the forearm and upper arm on the affected side of the human body is collected by the electromyography sensor, and the sEMG signal is used to perform real-time force recognition through the end force estimation model, and the estimated force is used as the interactive force input in the admittance controller. Linear and circular compliance training trajectories were planned, and impedance parameter characteristics were analyzed to obtain admittance control parameters suitable for upper limb passive rehabilitation training. The results show that the force estimation method based on sEMG, combined with the compliance control strategy, improves the interactive ability of upper limb rehabilitation training, ensures the personal safety of users, and makes the training more scientific and effective.
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Lyu, H., Gu, YL., Lin, G., Zhang, DH., Zhao, XG. (2022). Research on Compliant Rehabilitation Strategy of Upper Limb Rehabilitation Robot Based on sEMG. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13458. Springer, Cham. https://doi.org/10.1007/978-3-031-13841-6_37
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DOI: https://doi.org/10.1007/978-3-031-13841-6_37
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