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

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

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.

OriginalspracheEnglisch
TitelKI 2009
UntertitelAdvances in Artificial Intelligence - 32nd Annual German Conference on AI, Proceedings
Seiten339-346
Seitenumfang8
DOIs
PublikationsstatusVeröffentlicht - 2009
Veranstaltung32nd Annual German Conference on Artificial Intelligence, KI 2009 - Paderborn, Deutschland
Dauer: 15 Sept. 200918 Sept. 2009

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band5803 LNAI
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

Konferenz

Konferenz32nd Annual German Conference on Artificial Intelligence, KI 2009
Land/GebietDeutschland
OrtPaderborn
Zeitraum15/09/0918/09/09

Fingerprint

Untersuchen Sie die Forschungsthemen von „P300 detection based on feature extraction in on-line brain-computer interface“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren