BCI and Multimodal Feedback Based Attention Regulation for Lower Limb Rehabilitation

Both motor and cognitive function rehabilitation benefits can be improved significantly by patients' active participation. However, post-stroke patients, especially with attention-deficit disorders, can hardly engage in training for a longer time. In order to improve patients' attention focused on the training, an attention regulation system based on the brain-machine interface (BCI) and multimodal feedback is proposed for post-stroke lower limb rehabilitation. First, an interactive speed-tracking riding game is designed to increase the training challenge and patients' neural engagement. The character's riding speed, which is synchronized with patients' actual cycling speed, is displayed on the screen in real time. And patients' attention can further be enhanced when they try their best to track the reference speed curve. Second, an attention classifier is designed and trained by using subjects' EEG signals, which are acquired if they are tracking the reference speed curve or not. This classifier is finally applied to monitor subject's attention. If the subject is recognized with inadequate attention, sharp voice (auditory feedback) and red screen (visual feedback) will be given by the designed game to remind the subject to focus on the training. The contrast experiment results show that subjects' performance indicated by speed tracking accuracy and muscle activation can be improved significantly by using the attention regulation system. Moreover, the phenomenon of prominent decrease in theta rhythm and increase in beta rhythm can be found, which is consistent with previous research and further validates the feasibility of the proposed system in attention enhancement.