Please use this identifier to cite or link to this item: http://hdl.handle.net/11400/4938
Title: Intracranial current signals classification using multivariate autoregressive modeling and simulated annealing technique
Authors: Βάσιος, Χρήστος
Ματσόπουλος, Γεώργιος Κ.
Βεντούρας, Ερρίκος Μ.
Παπαγεωργίου, Χαράλαμπος
Νικήτα, Κωνσταντίνα Σ.
Contributors: Κονταξάκης, Βασίλειος Π.
Χριστοδούλου, Γιώργος Ν.
Ουζούνογλου, Νικόλαος Κ.
Hamza, M.H. (Ed.)
Item type: Conference publication
Conference Item Type: Full Paper
Keywords: Brain;Cathode ray oscillographs;Εγκέφαλος;Κυματομορφές
Subjects: Medicine
Medical technology
Ιατρική
Ιατρικά όργανα και εξοπλισμός
Issue Date: 28-Jan-2015
Publisher: IASTED
Abstract: Intracranial currents computed by the scalp-recorded ERPs, provide information on the non-observable electrical phenomena taking place in the brain, related to the cognitive mechanisms induced by the experimental task used in the ERP recording procedure. The use of current source waveforms, as input in classification systems, may provide robust classifiers due to the immediate relationship of the current sources to the brain electrical activity related to cognitive mechanisms. In the present work, a new method for the classification of intracranial current sources is proposed, combining the Multivariate Autoregressive model with the Simulated Annealing technique, in order to extract optimum features, in terms of the classification rate. The classification is implemented using a three-layer neural network (NN) trained with the back-propagation algorithm. The system was applied in the classification of normal controls and schizophrenic patients, providing classification rates of up to 100%. Furthermore, the clustering of intracranial source locations providing best classification performance may indicate relationships between the brain areas corresponding to these locations and pathological mechanisms.
Description: Proceedings of the International Conference on Biomedical Engineering of the IASTED (International Association of Science and Technology for Development)
Language: English
Citation: Vasios, C., Matsopoulos, G., Ventouras, E., Papageorgiou, C., Nikita, K., et al. (2003). Intracranial current signals classification using multivariate autoregressive modeling and simulated annealing technique. In the International Conference on Biomedical Engineering of the IASTED (International Association of Science and Technology for Development). pp. 33-38. IASTED: Salzburg, 2003.
Conference: International Conference on Biomedical Engineering of the IASTED
Access scheme: Embargo
License: Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες
URI: http://hdl.handle.net/11400/4938
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