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.
The Impact of Three-Week Passive Robotic Hand Therapy on Stroke Patients
Lect.Notes Computer
International Conference on Intelligent Robotics and Applications ; 2023 ; Hangzhou, China July 05, 2023 - July 07, 2023
21.10.2023
11 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Electroencephalography , electromyography , robotic hand therapy Computer Science , Artificial Intelligence , Software Engineering/Programming and Operating Systems , Computer Applications , Computer Communication Networks , Special Purpose and Application-Based Systems , User Interfaces and Human Computer Interaction
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