PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Attentional Modulation of Auditory Event-Related Potentials in a Brain-Computer Interface
N.J. Hill, Thomas Navin Lal, K. Bierig, N. Birbaumer and Bernhard Schölkopf
IEEE International Workshop on Biomedical Circuits and Systems (BioCAS04) 2004.

Abstract

Motivated by the particular problems involved in communicating with "locked-in" paralysed patients, we aim to develop a brain-computer interface that uses auditory stimuli. We describe a paradigm that allows a user to make a binary decision by focusing attention on one of two concurrent auditory stimulus sequences. Using Support Vector Machine classification and Recursive Channel Elimination on the independent components of averaged event-related potentials, we show that an untrained user's EEG data can be classified with an encouragingly high level of accuracy. This suggests that it is possible for users to modulate EEG signals in a single trial by the conscious direction of attention, well enough to be useful in BCI.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Brain Computer Interfaces
ID Code:408
Deposited By:Thomas Navin Lal
Deposited On:19 December 2004