P300 detection based on feature extraction in on-line brain-computer interface

Nikolay Chumerin, Nikolay V. Manyakov, Adrien Combaz, Johan A.K. Suykens, Refet Firat Yazicioglu, Tom Torfs, Patrick Merken, Herc P. Neves, Chris Van Hoof, Marc M. Van Hulle

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We propose a new EEG-based wireless brain computer interface (BCI) with which subjects can "mind-type" text on a computer screen. The application is based on detecting P300 event-related potentials in EEG signals recorded on the scalp of the subject. The BCI uses a simple classifier which relies on a linear feature extraction approach. The accuracy of the presented system is comparable to the state-of-the-art for on-line P300 detection, but with the additional benefit that its much simpler design supports a power-efficient on-chip implementation.

Original languageEnglish
Title of host publicationKI 2009
Subtitle of host publicationAdvances in Artificial Intelligence - 32nd Annual German Conference on AI, Proceedings
Pages339-346
Number of pages8
DOIs
Publication statusPublished - 2009
Event32nd Annual German Conference on Artificial Intelligence, KI 2009 - Paderborn, Germany
Duration: 15 Sept 200918 Sept 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5803 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference32nd Annual German Conference on Artificial Intelligence, KI 2009
Country/TerritoryGermany
CityPaderborn
Period15/09/0918/09/09

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