Event-related potentials processing using independent component analysis technique

dc.contributor.author	Μοάτσος, Μ.	el
dc.contributor.author	Βεντούρας, Ερρίκος Μ.	el
dc.contributor.author	Παπαγεωργίου, Χαράλαμπος	el
dc.contributor.author	Λιάππας, Ιωάννης Α.	el
dc.contributor.author	Νικολάου, Χρυσούλα	el
dc.date.accessioned	2015-01-26T11:39:31Z
dc.date.issued	2015-01-26
dc.identifier.uri	http://hdl.handle.net/11400/4764
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject	Electroencephalography
dc.subject	Independent component analysis
dc.subject	Ηλεκτροεγκεφαλογράφημα
dc.subject	Ανάλυση ανεξάρτητων συνιστωσών
dc.title	Event-related potentials processing using independent component analysis technique	en
heal.type	conferenceItem
heal.secondaryTitle	application to 6 month abstinent addicts	en
heal.generalDescription	Proceedings of the 4th European Symposium on Biomedical Engineering	en
heal.classification	Medicine
heal.classification	Computer engineering
heal.classification	Ιατρική
heal.classification	Μηχανική υπολογιστών
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85029495
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Ηλεκτρολογική μηχανική
heal.keywordURI	http://lod.nal.usda.gov/19230
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh2011000546
heal.contributorName	Ραμπαβίλας, Ανδρέας Ν.	el
heal.contributorName	Ουζούνογλου, Νικόλαος Κ.	el
heal.dateAvailable	10000-01-01
heal.language	en
heal.access	forever
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2004
heal.bibliographicCitation	Moatsos, M., Ventouras, E., Papageorgiou, C., Liappas, I.A., Nikolaou, C., et al. (2004). Event-related potentials processing using independent component analysis technique: application to 6 month abstinent addicts. In the 4th European Symposium on Biomedical Engineering. University of Patras: Patras, 2004.	en
heal.abstract	Electroencephalographic Event-Related Potentials (ERPs) present special interest for investigating cognitive processes. ERP curves contain peaks called components, such as the P600 component. P600 may be present in the averaged ERP waveform as a not-easily discernible secondary peak. In order to extract the P600 component, Independent Component Analysis (ICA) is used. ICA is a method used for solving the Blind Source Separation (BSS) problem, based on the assumption that the sources are statisti cally independent. The focus of the present study was to select a subset of independent components (ICs) for the reconstruction of the averaged ERPs in the original electrode recording positions and in the time frame of the P600 component. Two empirical criteria are used for the selection of the IC’s; the first criterion is based on the temporal proximity of the original P600 and the IC projection that reconstructs the P600 component and the second criterion is maximizing the reconstructed P600 amplitude based on the selection of a combination of IC projections using up to a preselected maximum number of them. The techniques are tested on ERPs recorded from healthy subjects and heroin addicts.	en
heal.fullTextAvailability	true
heal.conferenceName	European Symposium on Biomedical Engineering	en
heal.conferenceItemType	full paper