Abstract
Functional electrical stimulation (FES) is an effective approach to restore hand movement function for patients with stroke. In this paper, a multi-electrode hand rehabilitation system is presented. Iterative learning control (ILC) with forgetting factor algorithm is employed to achieve an accuracy position control of multi-joint hand movement. A mapping matrix is identified to model the gains from the multi-electrode inputs to the multiple joints of the hand. The convergence conditions of ILC with forgetting factor for the proposed method are analyzed. Finally, experiments on healthy subjects are carried out to verify the performance of the proposed control method.
This work is partially supported by the National Natural Science Foundation of China (62103376), China Postdoctoral Science Foundation (2018M632801), Science & Technology Research Project in Henan Province of China (212102310253) and Joint fund of Science & Technology Department of Liaoning Province and State Key Laboratory of Robotics (2021-KF-22-10). & National Natural Science Foundation of China (U1813214).
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Zhao, G., Zeng, Q., Huo, B., Zhao, X., Zhang, D. (2022). FES-Based Hand Movement Control via Iterative Learning Control with Forgetting Factor. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13456. Springer, Cham. https://doi.org/10.1007/978-3-031-13822-5_25
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DOI: https://doi.org/10.1007/978-3-031-13822-5_25
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