Ανάπτυξη συστημάτων αναγνώρισης μορφών προκλητών δυναμικών και ενδοκρανιακών ρευμάτων

dc.contributor.author	Καλατζής, Ιωάννης	el
dc.contributor.author	Πήλιουρας, Νικόλαος	el
dc.contributor.author	Κάβουρας, Διονύσης Α.	el
dc.contributor.author	Παπαγεωργίου, Χαράλαμπος	el
dc.contributor.author	Κανδαράκης, Ιωάννης Σ.	el
dc.date.accessioned	2015-02-06T11:38:54Z
dc.date.available	2015-02-06T11:38:54Z
dc.date.issued	2015-02-06
dc.identifier.uri	http://hdl.handle.net/11400/5738
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	Classification systems
dc.subject	Pattern recognition
dc.subject	Συστήματα ταξινόμησης
dc.subject	Αναγνώριση προτύπων
dc.title	Ανάπτυξη συστημάτων αναγνώρισης μορφών προκλητών δυναμικών και ενδοκρανιακών ρευμάτων	el
heal.type	conferenceItem
heal.generalDescription	Πρακτικά 1ου Συνεδρίου ΕΠΕΑΕΚ Αρχιμήδης	el
heal.classification	Medicine
heal.classification	Biomedical engineering
heal.classification	Ιατρική
heal.classification	Βιοϊατρική τεχνολογία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85014237
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Βιοϊατρική τεχνολογία
heal.keywordURI	http://skos.um.es/unescothes/C00619
heal.keywordURI	http://skos.um.es/unescothes/C02924
heal.contributorName	Σπυρόπουλος, Β.	el
heal.contributorName	Λιάππας, Ιωάννης Α.	el
heal.contributorName	Νικολάου, Χρυσούλα	el
heal.contributorName	Ραμπαβίλας, Ανδρέας Ν.	el
heal.contributorName	Σολδάτος, Κωνσταντίνος Ρ.	el
heal.contributorName	Βεντούρας, Ερρίκος Μ.	el
heal.language	el
heal.access	campus
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2005
heal.bibliographicCitation	Καλατζής, Ι., Πήλιουρας, Ν., Κάβουρας, Δ., Παπαγεωργίου, Χ., Κανδαράκης, Ι., κ.ά. (2005). Ανάπτυξη συστημάτων αναγνώρισης μορφών προκλητών δυναμικών και ενδοκρανιακών ρευμάτων. Στο 1ο Συνέδριο ΕΠΕΑΕΚ Αρχιμήδης. σελ.227-236. Τ.Ε.Ι. Αθήνας, 2005.	el
heal.abstract	Pattern recognition classification schemes were developed and they were applied in a number of studies in an attempt to distinguish between patients from several neurological or psychological disorders and normal controls and to locate brain areas of possible dysfunction. Clinical material comprised patients with depression, patients with obsessive-compulsion disorder, one-month abstinent alcoholics, one-month abstinent heroin addicts and healthy controls. All subjects were evaluated by a computerized version of the digit span Wechsler test. The EEG activity was recorded and digitized from 15 scalp electrodes (leads) and signals were inverted into intracranial currents. Nineteen features related to the shape of the waveform were generated and were used as input to the classification schemes developed, which comprised single classifiers as well as more complex classification schemes. The best overall accuracies, achieved in specific brain areas, ranged between 94% and 100%, indicating that these techniques may significantly facilitate computer-aided analysis of EEG signals and suggesting specific brain areas as relative to the corresponding disorders.	en
heal.publisher	[χ.ό.]	el
heal.fullTextAvailability	true
heal.conferenceName	Συνεδρίου ΕΠΕΑΕΚ Αρχιμήδης	el
heal.conferenceItemType	full paper