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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
  • KU Leuven
  • IMEC

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

19 Citations (Scopus)

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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