Both motor and cognitive function rehabilitation
benefits can be improved significantly by patients’ active participation. However, post-stroke patients, especially with attentiondeficit 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.