A local neural classifier for the recognition of EEG patterns associated to mental tasks

Authors:
J. del R Millan;J. Mourino;M. Franze;F. Cincotti;M. Varsta;J. Heikkonen;F. Babiloni
Affiliations:
Joint Res. Centre, Comm. of the Eur. Communities, Ispra;-;-;-;-;-;-
Venue:
IEEE Transactions on Neural Networks
Year:
2002

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Abstract

This paper proposes a novel and simple local neural classifier for the recognition of mental tasks from on-line spontaneous EEG signals. The proposed neural classifier recognizes three mental tasks from on-line spontaneous EEG signals. Correct recognition is around 70%. This modest rate is largely compensated by two properties, namely low percentage of wrong decisions (below 5%) and rapid responses (every 1/2 s). Interestingly, the neural classifier achieves this performance with a few units, normally just one per mental task. Also, since the subject and his/her personal interface learn simultaneously from each other, subjects master it rapidly (in a few days of moderate training). Finally, analysis of learned EEG patterns confirms that for a subject to operate satisfactorily a brain interface, the latter must fit the individual features of the former