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EEG Error-Related Potentials Detection With A Bayesian Filter

Abstract : Several studies describe evoked EEG potentials elicited when a subject is aware of an erroneous decision either taken by him or by an external interface. This paper try to detect Error-related potentials (ErrP) elicited when a human user want to monitors an external system upon which he has no control whatsoever. To this end we use a Bayesian filter to classify erroneous or correct events. On average over three subjects, the proposed probabilistic classifier achieves single-trial classification of 85% for correct trials and 71% for erroneous trials.
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Submitted on : Thursday, March 12, 2009 - 3:07:26 PM
Last modification on : Thursday, October 21, 2021 - 3:53:30 AM
Long-term archiving on: : Thursday, June 30, 2011 - 11:03:58 AM


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  • HAL Id : inria-00365266, version 1



Jean-Marc Bollon, Ricardo Chavarriaga, José Millán, Pierre Bessiere. EEG Error-Related Potentials Detection With A Bayesian Filter. 4th International IEEE EMBS Conference on Neural Engineering, Apr 2009, Antalya, Turkey. ⟨inria-00365266⟩



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