Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform

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dc.contributor.authorPolat, Kemal
dc.contributor.authorGuenes, Salih
dc.date.accessioned2020-03-26T17:17:07Z
dc.date.available2020-03-26T17:17:07Z
dc.date.issued2007
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThe aim of this study is to detect epileptic seizure in EEG signals using a hybrid system based on decision tree classifier and fast Fourier transform (FFT). The present study proposes a hybrid system with two stages: feature extraction using FFT and decision making using decision tree classifier. The detection of epileptiform, discharges in the electroencephalogram (EEG) is an important part in the diagnosis of epilepsy. All data set were obtained from EEG signals of healthy subjects and subjects suffering from epilepsy diseases. For healthy subjects is background EEG (scalp) with open eyes and for epileptic patients correspond to a seizure recorded in hippocampus (epileptic focus) with depth electrodes. The evolution of proposed system was conducted using k-fold cross-validation, classification accuracy, and sensitivity and specificity values. We have obtained 98.68% and 98.72% classification accuracies using 5- and 10-fold cross-validation. The stated results show that the proposed method could point out the ability of design of a new intelligent assistance diagnosis system. (C) 2006 Elsevier Inc. All rights reserved.en_US
dc.identifier.doi10.1016/j.amc.2006.09.022en_US
dc.identifier.endpage1026en_US
dc.identifier.issn0096-3003en_US
dc.identifier.issn1873-5649en_US
dc.identifier.issue2en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1017en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.amc.2006.09.022
dc.identifier.urihttps://hdl.handle.net/20.500.12395/21269
dc.identifier.volume187en_US
dc.identifier.wosWOS:000248545300048en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherELSEVIER SCIENCE INCen_US
dc.relation.ispartofAPPLIED MATHEMATICS AND COMPUTATIONen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectelectroencephalogram (EEG)en_US
dc.subjectepileptic seizureen_US
dc.subjectFFTen_US
dc.subjectdecision tree classifieren_US
dc.subjectk-Fold cross-validationen_US
dc.titleClassification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transformen_US
dc.typeArticleen_US

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