Abstract
Robotic hand therapy is widely used in rehabilitation for patients with hand dysfunction caused by stoke. However, the effectiveness of passive robotic hand training for rehabilitation is still unknown. In this study, we assessed the impact of three-week passive robotic hand therapy on stroke patients based on electroencephalography (EEG) and electromyography (EMG). We employed localization techniques to identify the source of electrical activity and compared the brain activity between the left and right regions of sensorimotor. Despite the limited improvements in hand function, the results showed that there was an overall improvement in brain activity. Although no significant difference was observed in the change of brain activity at the sensorimotor regions after the training in three movement modes, the EEG-EMG coherence in the beta and gamma frequency bands were increased after training in the active mode, suggesting an increase in the efficiency of nerve signals driving muscle activity. This study contributes to a better understanding of the effectiveness of various neurological rehabilitation training methods for stroke patients undergoing robotic hand therapy.
X. Li and M. Zheng—These authors contributed equally.
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Acknowledgement
This work was supported by the National Natural Science Foundation of China under Grant 62201515 and Grant 12101570, the China Postdoctoral Science Foundation under Grant 2021M702974, and Key Research Project of Zhejiang Lab (2022KI0AC01).
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Li, X. et al. (2023). The Impact of Three-Week Passive Robotic Hand Therapy on Stroke Patients. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14267. Springer, Singapore. https://doi.org/10.1007/978-981-99-6483-3_21
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