Attention-controlled assistive wrist rehabilitation using a low-cost EEG sensor

Li, Min and Liang, Ziting and He, Bo and Zhao, Chen-Guang and Yao, Wei and Xu, Guanghua and Xie, Jun and Cui, Lei (2019) Attention-controlled assistive wrist rehabilitation using a low-cost EEG sensor. IEEE Sensors Journal, 9 (15). pp. 6497-6507. 8686128. ISSN 1530-437X

[thumbnail of Li-etal-IEEE-Sesors-2019-Attention-controlled-assistive-wrist-rehabilitation-using-a-low-cost-EEG-sensor]
Text (Li-etal-IEEE-Sesors-2019-Attention-controlled-assistive-wrist-rehabilitation-using-a-low-cost-EEG-sensor)
Accepted Author Manuscript

Download (939kB)| Preview


    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.