Classification of EEG Signals Using Hilbert-Huang Transform-Based Deep Neural Networks

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dc.contributor.authorZan, Hasan
dc.contributor.authorYildiz, Abdulnasir
dc.contributor.authorOzerdem, Mehmet Sirac
dc.date.accessioned2024-04-24T17:33:20Z
dc.date.available2024-04-24T17:33:20Z
dc.date.issued2019
dc.departmentDicle Üniversitesien_US
dc.description4th International Conference on Computer Science and Engineering (UBMK) -- SEP 11-15, 2019 -- Samsun, TURKEYen_US
dc.description.abstractEpilepsy is one of the most common neurologic disease. Electroencephalogram (EEG) contains physiologic and pathological information related human nervous system. EEG signals used in this study are obtained from Bonn University, Department of Epileptology EEG database. Original database has five subsets (A, B, C, D, E). Data have been reorganized into three groups which are healthy (AB), interictal (CD) and ictal EEG signals. Furthermore, in order to examine effect of signal length on classification performance, three different lengths are used. Hilbert-Huang transform is applied to the signals and they are represented as image files. Then, generated images are fed into deep neural networks with five different structures for classification. Accuracy is calculated for all cases to asses performance of proposed method. it is clear that successful results could be obtained using Hilbert-Huang transform along with deep learning networks.en_US
dc.description.sponsorshipIEEE,IEEE Turkey Secten_US
dc.identifier.endpage289en_US
dc.identifier.isbn978-1-7281-3964-7
dc.identifier.scopus2-s2.0-85076216208
dc.identifier.scopusqualityN/A
dc.identifier.startpage285en_US
dc.identifier.urihttps://hdl.handle.net/11468/20631
dc.identifier.wosWOS:000609879900054
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2019 4th International Conference on Computer Science and Engineering (Ubmk)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHilbert-Haung Transformen_US
dc.subjectEegen_US
dc.subjectEpilepsyen_US
dc.subjectDeep Learningen_US
dc.subjectClassificationen_US
dc.titleClassification of EEG Signals Using Hilbert-Huang Transform-Based Deep Neural Networksen_US
dc.titleClassification of EEG Signals Using Hilbert-Huang Transform-Based Deep Neural Networks
dc.typeConference Objecten_US

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