Local neural classifier for EEG-based recognition of mental tasks

This paper proposes a new local neural classifier for the recognition of mental tasks from on-line spontaneous EEG signals. The classifier is embedded in a portable brain-computer interface called ABI, which has been evaluated with 4 young healthy persons. Subjects' performance is analyzed off-line and, for three of them, also online in the presence of biofeedback. The proposed ABI recognizes three mental tasks from on-line spontaneous EEG signals. Correct recognition is around 70%. This modest rate is largely compensated by two properties of ABI: wrong responses are below 5% and it makes decisions every 1/2 second. Also, since the subject and his/her personal ABI learn simultaneously from each other, subjects master it rapidly: one of the subjects achieved excellent control in just 5 days of training.