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An Auditory Paradigm for Brain-Computer Interfaces

MPG-Autoren
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Hill,  NJ
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Lal,  TN
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Bierig,  K
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Schölkopf,  B
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Hill, N., Lal, T., Bierig, K., Birbaumer, N., & Schölkopf, B. (2005). An Auditory Paradigm for Brain-Computer Interfaces. Advances in Neural Information Processing Systems, 569-576.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-D517-8
Zusammenfassung
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.