Please use this identifier to cite or link to this item: http://hdl.handle.net/11400/4730
Title: Cross-validated classification of intracranial sources extracted by BET-ART method
Authors: Βάσιος, Χρήστος
Ματσόπουλος, Γεώργιος Κ.
Βεντούρας, Ερρίκος Μ.
Παπαγεωργίου, Χαράλαμπος
Κονταξάκης, Βασίλειος Π.
Contributors: Νικήτα, Κωνσταντίνα Σ.
Ουζούνογλου, Νικόλαος Κ.
Item type: Conference publication
Conference Item Type: Full Paper
Keywords: Electroencephalography;Bioelectric potentials;Ηλεκτροεγκεφαλογραφία;Βιοηλεκτρικό δυναμικό
Subjects: Medicine
Medical technology
Ιατρική
Ιατρική τεχνολογία
Issue Date: 26-Jan-2015
2005
Publisher: IEEE
Abstract: In the present paper, a new methodological approach, for the classification of first episode schizophrenic patients (FES) against normal controls, is proposed. The first step of the methodology applied is the feature extraction, which is based on the combination of the multivariate autoregressive model with the simulated annealing technique, in order to extract optimum features, in terms of classification rate. The classification, as the second step of the methodology, is implemented by means of an artificial neural network (ANN) trained with the back-propagation algorithm under "leave-one-out cross-validation". The ANN is a multi-layer perceptron, the architecture of which, is selected after a detailed search. The proposed methodology has been applied for the classification of FES patients and normal controls using as input signals the Intracranial current sources obtained by the inversion of ERPs using an algebraic reconstruction technique. Results by implementing the proposed methodology provide classification rates of up to 93.1%
Description: Proceedings of the 2nd International IEEE-EMBS Conference on Neural Engineering
Language: English
Citation: Vasios , C., Matsopoulos, G., Ventouras, E., Papageorgiou, C., Kontaxakis, V., et al. (2005). Cross-validated classification of intracranial sources extracted by BET-ART method. In the 2nd International IEEE-EMBS Conference on Neural Engineering. pp. 140-143. IEEE Engineering in Medicine and Biology Society: Arlington, 16th-19th March 2005.
Conference: International IEEE-EMBS Conference on Neural Engineering
Access scheme: Embargo
License: Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες
URI: http://hdl.handle.net/11400/4730
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