A novel system for automatic detection of K-complexes in sleep EEG

Basit Öğe Kaydı
dc.contributor.authorYucelbas, Cuneyt
dc.contributor.authorYucelbas, Sule
dc.contributor.authorOzsen, Seral
dc.contributor.authorTezel, Gulay
dc.contributor.authorKuccukturk, Serkan
dc.contributor.authorYosunkaya, Sebnem
dc.date.accessioned2020-03-26T19:52:45Z
dc.date.available2020-03-26T19:52:45Z
dc.date.issued2018
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractSleep staging process is applied to diagnose sleep-related disorders by sleep experts through analyzing sleep signals such as electroencephalogram (EEG), electrooculogram and electromyogram of subjects and determining the stages in 30-s-length time parts of sleep named as epochs. Subjects enter several stages during the sleep, and N-REM2 is one of them which has also the highest duration among the other stages. Approximately half of the sleep consists of N-REM2. One of the important parameters in determining N-REM2 stage is K-complex (Kc). In this study, some time and frequency analysis methods were used to determine the locations of Kcs, automatically. These are singular value decomposition (SVD), variational mode decomposition and discrete wavelet transform. The performance of them in detecting Kcs was compared. Furthermore, systems with combinations of these methods were presented with logic AND operations. The EEG recordings of seven subjects were obtained from the Sleep Research Laboratory of Necmettin Erbakan University. A database with total 359 Kcs in 320 epochs was prepared from the recordings. According to the results, the highest average recognition rate was found as 92.29% for the SVD method. Thanks to this study, the sleep experts can find out whether there were Kcs in related epochs and also know their locations in these epochs, automatically. Also, it will help automatic sleep stage classification systems.en_US
dc.description.sponsorshipScientific and Technological Research Council of TurkeyTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [113E591]; Scientific Research Projects Coordination Unit of Selcuk UniversitySelcuk Universityen_US
dc.description.sponsorshipThis study is supported by the Scientific and Technological Research Council of Turkey (project no. 113E591) and the Scientific Research Projects Coordination Unit of Selcuk University.en_US
dc.identifier.doi10.1007/s00521-017-2865-3en_US
dc.identifier.endpage157en_US
dc.identifier.issn0941-0643en_US
dc.identifier.issn1433-3058en_US
dc.identifier.issue8en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage137en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s00521-017-2865-3
dc.identifier.urihttps://hdl.handle.net/20.500.12395/36277
dc.identifier.volume29en_US
dc.identifier.wosWOS:000427799900011en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSPRINGER LONDON LTDen_US
dc.relation.ispartofNEURAL COMPUTING & APPLICATIONSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectDWTen_US
dc.subjectSleep EEGen_US
dc.subjectK-complexen_US
dc.subjectSVDen_US
dc.subjectVMDen_US
dc.titleA novel system for automatic detection of K-complexes in sleep EEGen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu