SVM-based discrimination of one-month abstinent alcoholics from healthy controls using the P600 component of ERP signals

dc.contributor.author	Καλατζής, Ιωάννης	el
dc.contributor.author	Πήλιουρας, Νικόλαος	el
dc.contributor.author	Βεντούρας, Ερρίκος Μ.	el
dc.contributor.author	Παπαγεωργίου, Χαράλαμπος	el
dc.contributor.author	Λιάππας, Ιωάννης Α.	el
dc.date.accessioned	2015-01-26T12:25:34Z
dc.date.issued	2015-01-26
dc.identifier.uri	http://hdl.handle.net/11400/4768
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	Alcoholics
dc.subject	Pattern recognition
dc.subject	Αλκοολικοί
dc.subject	Αναγνώριση προτύπων
dc.title	SVM-based discrimination of one-month abstinent alcoholics from healthy controls using the P600 component of ERP signals	en
heal.type	conferenceItem
heal.generalDescription	Proceedings of the 1st International Conference “From Scientific Computing to Computational Engineering” (1ST IC-SCCE) (CD-ROM).	en
heal.classification	Medicine
heal.classification	Human physiology
heal.classification	Ιατρική
heal.classification	Ανθρώπινη φυσιολογία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85062884
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Ανθρώπινη φυσιολογία
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh2008108988
heal.contributorName	Νικολάου, Χρυσούλα	el
heal.contributorName	Ραμπαβίλας, Ανδρέας Ν.	el
heal.contributorName	Κάβουρας, Διονύσης Α.	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	Kalatzis, I., Piliouras, N., Ventouras, E., Papageorgiou, C., Liappas, I., et al. (2004). SVM-based discrimination of one-month abstinent alcoholics from healthy controls using the P600 component of ERP signals. In the 1st International Conference “From Scientific Computing to Computational Engineering. University of Patras: Athens, 8th-10th September 2004.	en
heal.abstract	The aim of this study was to design a computer-based classification system capable of distinguishing one-month abstinent alcoholics from normal controls by Event-related potential (ERP) signals using the P600 component. Clinical material comprised twenty one-month abstinent alcoholics and an equal number of gender and aged-matched healthy controls. All subjects were evaluated by a computerized version of the digit span Wechsler test. EEG activity was recorded and digitized from 15 scalp electrodes (leads). A dedicated computer software was developed and it was used to read the ERP signals and to calculate features related to the P600 component (500-800 ms) of the ERP signal. Nineteen features were generated and were employed in the design of an optimum SVM-classifier at each lead. The outcomes of those SVM-classifiers were selected by a majority-vote engine (MVE), which assigned each subject to either the normal or alcoholic classes. MVE-classification accuracy was 97.5% when using all leads and 92.5% or 77.5% when using only the right or left scalp leads respectively. These findings provide evidence of right hemisphere dysfunction in alcoholics affecting the processing of information that assigns a specific response to a specific stimulus, as those mechanisms are reflected by the P600 component of ERPs.	en
heal.fullTextAvailability	true
heal.conferenceName	International Conference From Scientific Computing to Computational Engineering	en
heal.conferenceItemType	full paper