Epileptic state detection : Pre-ictal, inter-ictal, ictal

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dc.contributor.authorYayık, Apdullah
dc.contributor.authorYıldırım, Esen
dc.contributor.authorKutlu, Yakup
dc.contributor.authorYıldırım, Serdar
dc.date.accessioned2019-07-16T16:00:26Z
dc.date.available2019-07-16T16:00:26Z
dc.date.issued2015
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description.abstractEpileptic seizure detection and prediction from electroencephalography (EEG) is a vital area of research. In this study, SecondOrder Difference Plot (SODP) is used to extract features based on consecutive difference of time domain values from three states of EEG (pre-ictal, ictal and inter-ictal), and Multi-Layer Neural Network classifier is used to classify these three classes. The proposed technique is tested on a publicly available EEG database and classified with Naive Bayes and k-nearest neighbor classifiers. As a result, it is shown that overall accuracy of 98.70% can be achieved by using the proposed system with Neural Network classifier.en_US
dc.description.abstractEpileptic seizure detection and prediction from electroencephalography (EEG) is a vital area of research. In this study, SecondOrder Difference Plot (SODP) is used to extract features based on consecutive difference of time domain values from three states of EEG (pre-ictal, ictal and inter-ictal), and Multi-Layer Neural Network classifier is used to classify these three classes. The proposed technique is tested on a publicly available EEG database and classified with Naive Bayes and k-nearest neighbor classifiers. As a result, it is shown that overall accuracy of 98.70% can be achieved by using the proposed system with Neural Network classifier.en_US
dc.identifier.endpage18en_US
dc.identifier.issn2147-6799
dc.identifier.issue1en_US
dc.identifier.startpage14en_US
dc.identifier.urihttps://trdizin.gov.tr/publication/paper/detail/TVRreU56Y3dNQT09
dc.identifier.urihttps://hdl.handle.net/20.500.12483/2326
dc.identifier.volume3en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.relation.ispartofInternational Journal of Intelligent Systems and Applications in Engineeringen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US]
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBilgisayar Bilimlerien_US
dc.subjectYapay Zekaen_US
dc.titleEpileptic state detection : Pre-ictal, inter-ictal, ictalen_US
dc.typeArticleen_US

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