bibtype	C - Conference Paper (international conference)
ARLID	0040021
utime	20240103182624.9
mtime	20060815235959.9
title (primary) (eng)	Identification of epileptic activity in electroencephalograms using four techniques of independent component analysis
specification	page_count 3 s.
serial	ARLID cav_un_epca*0076638 ISBN 80-214-3152-0 title Analysis of Biomedical Signals and Images. BIOSIGNAL 2006 page_num 166-168 publisher place Brno name University of Technology year 2006 editor name1 Jan name2 J. editor name1 Kozumplík name2 J. editor name1 Provazník name2 I.
title (cze)	Separace epilepticke aktivity v zaznamech elektroencefalografu pomoci ctyr metod analyzy nezavislych komponent.
keyword	electroencephalogram
keyword	blind source separation
keyword	independent component analysis
keyword	epilepsy
keyword	ictus
author (primary)	ARLID cav_un_auth*0101212 name1 Tichavský name2 Petr institution UTIA-B full_dept Department of Stochastic Informatics fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author	ARLID cav_un_auth*0213020 name1 Nielsen name2 Jan institution UTIA-B fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author	ARLID cav_un_auth*0215799 name1 Krajča name2 V. country CZ
COSATI	12B
cas_special	project project_id 1M0572 agency GA MŠk ARLID cav_un_auth*0001814 project project_id 1ET101210512 agency GA AV ČR country CZ ARLID cav_un_auth*0215801 research CEZ:AV0Z10750506 abstract (eng) The presented study aims to evaluate possibility of separation of epileptic activity from the EEG data using two well known and two recently proposed algorithms for independent component analysis (ICA): FastICA, EFICA, SOBI and WASOBI. All these techniques are shown to allow to concentrate an epileptic activityin two epilepsy-related independent components out of 19 channel EEG recordings. Among the techniques, the WASOBI was shown to be a most effective one. abstract (cze) V clanku je zkoumana moznost separace epilepticke aktivity v EEG zaznamech pomoci dvou klasickych a dvou nedavno navrzenych metod slepe separace: FastICA, EFICA, SOBI a WASOBI. Tyto metody umoznuji pri zpracovani 19-kanaloveho EEG zaznamu epileptickou aktivitu vice-mene uspesne koncentrovat ve dvou signalovych komponetach. Mezi temito metodami se algoritmus WASOBI jevi jako ten ktery umoznuje nejpresnejsi separaci. action ARLID cav_un_auth*0215800 name Biosignal 2006 place Brno dates 28.06.2006-30.06.2006 country CZ reportyear 2007 RIV FH permalink http://hdl.handle.net/11104/0133890 arlyear 2006 mrcbU63 cav_un_epca*0076638 Analysis of Biomedical Signals and Images. BIOSIGNAL 2006 80-214-3152-0 166 168 Brno University of Technology 2006 mrcbU67 Jan J. 340 mrcbU67 Kozumplík J. 340 mrcbU67 Provazník I. 340