Institute of Information Theory and Automation

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Bibliography

Conference Paper (international conference)

Identification of epileptic activity in electroencephalograms using four techniques of independent component analysis

Tichavský Petr, Nielsen Jan, Krajča V.

: Analysis of Biomedical Signals and Images. BIOSIGNAL 2006, p. 166-168 , Eds: Jan J., Kozumplík J., Provazník I.

: Biosignal 2006, (Brno, CZ, 28.06.2006-30.06.2006)

: CEZ:AV0Z10750506

: 1M0572, GA MŠk, 1ET101210512, GA AV ČR

: electroencephalogram, blind source separation, independent component analysis, epilepsy, ictus

(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.

(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.

: 12B

: FH

2019-01-07 08:39