Spatial Tactile Brain-Computer Interface Paradigm Applying Vibration Stimuli to Large Areas of User's Back
This work addresses communication challenges for ALS patients by enabling device control through brain activity, representing an incremental advancement in stimulus-driven BCI methods.
The researchers tackled the problem of augmenting communication abilities for amyotrophic lateral sclerosis (ALS) patients by developing a brain-computer interface (BCI) that uses vibration stimuli on the user's back to elicit P300 responses from EEG data, achieving very accurate classification of these responses in psychophysical and online experiments.
We aim at an augmentation of communication abilities of amyotrophic lateral sclerosis (ALS) patients by creating a brain-computer interface (BCI) which can control a computer or other device by using only brain activity. As a method, we use a stimulus-driven BCI based on vibration stimuli delivered via a gaming pad to the user's back. We identify P300 responses from brain activity data in response to the vibration stimuli. The user's intentions are classified according to the P300 responses recorded in the EEG. From the results of the psychophysical and online BCI experiments, we are able to classify the P300 responses very accurately, which proves the effectiveness of the proposed method.