| Paper Name |
Attention-controlled assistive wrist rehabilitation using a low-cost EEG Sensor |
| Author |
Li, Min; Liang, Ziting; He, Bo; Zhao, Chen-Guang; Yao, Wei; Xu, Guanghua; Xie, J |
| Publication/Completion Time |
2019-04-11 |
| Magazine Name |
IEEE Sensors Journal |
| Vol |
19 (15) |
| Related articles |
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| Paper description |
It is essential to make sure patients be actively involved in motor training using robot-assisted rehabilitation to achieve better rehabilitation outcomes. This paper introduces an attention-controlled wrist rehabilitation method using a low-cost EEG sensor. Active rehabilitation training is realized using a threshold of the attention level measured by the low-cost EEG sensor as a switch for a flexible wrist exoskeleton assisting wrist flexion/extension and radial/ulnar deviation. We present a prototype implementation of this active training method and provide a preliminary evaluation. The feasibility of the attention-based control was proven with the overall actuation success rate of 95%. The experimental results also proved that the visual guidance was helpful for the users to concentrate on the wrist rehabilitation training; two types of visual guidance, namely looking at the hand motion shown on a video and looking at the user’s own hand, had no significant performance difference; a general threshold of a certain group of users can be utilized in the wrist robot control rather than a customized threshold to simplify the procedure. |
(创新港)
