Brain-Computer Interface (BCI) systems create a novel communication channel from the brain to an output device by bypassing conventional motor output pathways of nerves and muscles. Therefore they could provide a new communication and control option for paralyzed patients. Modern BCI technology is essentially based on techniques for the classification of single-trial brain signals. Here we present a novel technique that allows the simultaneous optimization of a spatial and a spectral filter enhancing discriminability of multi-channel EEG single-trials. The evaluation of 60 experiments involving 22 different subjects demonstrates the superiority of the proposed algorithm. Apart from the enhanced classification, the spatial and/or the spectral filter that are determined by the algorithmcan also be used for further analysis of the data, e.g., for source localization of the respective brain rhythms.
|Title of host publication
|Advances in Neural Information Processing Systems 18 - Proceedings of the 2005 Conference
|Number of pages
|Published - 2005
|2005 Annual Conference on Neural Information Processing Systems, NIPS 2005 - Vancouver, BC, Canada
Duration: 2005 Dec 5 → 2005 Dec 8
|Advances in Neural Information Processing Systems
|2005 Annual Conference on Neural Information Processing Systems, NIPS 2005
|05/12/5 → 05/12/8
Copyright 2013 Elsevier B.V., All rights reserved.
ASJC Scopus subject areas
- Computer Networks and Communications
- Information Systems
- Signal Processing