A new approach for estimation of obstructive sleep apnea syndrome

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dc.authoridTağluk, M. Emin/0000-0001-7789-6376
dc.authorwosidTağluk, M. Emin/ABH-1005-2020
dc.contributor.authorTagluk, M. Emin
dc.contributor.authorSezgin, Necmettin
dc.date.accessioned2024-08-04T20:32:41Z
dc.date.available2024-08-04T20:32:41Z
dc.date.issued2011
dc.departmentİnönü Üniversitesien_US
dc.description.abstractObstructive sleep apnea syndrome (OSAS) is a situation where repeatedly upper airway stops off while the respiratory effort continues during sleep at least for 10 s. Apart from polysomnography, many researchers have concentrated on exploring alternative methods for OSAS detection. However, not much work has been done on using non-Gaussian and nonlinear behavior of the electroencephalogram (EEG) signals. Bispectral analysis is an advanced signal processing technique particularly used for exhibiting quadratic phase-coupling that may arise between signal components with different frequencies. From this perspective, in this study, a new technique for recognizing patients with OSAS was introduced using bispectral characteristics of EEG signal and an artificial neural network (ANN). The amount of Quadratic phase coupling (QPC) in each subband of EEG (namely; delta, theta, alpha, beta and gamma) was calculated over bispectral density of EEG. Then, these QPCs were fed to the input of the designed ANN. The neural network was configured with two outputs: one for OSAS and one for estimation of normal situation. With this technique a global accuracy of 96.15% was achieved. The proposed technique could be used in designing automatic OSAS identification systems which will improve medical service. (C) 2010 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.eswa.2010.10.022
dc.identifier.endpage5351en_US
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.issue5en_US
dc.identifier.scopus2-s2.0-79151478952en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage5346en_US
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2010.10.022
dc.identifier.urihttps://hdl.handle.net/11616/95237
dc.identifier.volume38en_US
dc.identifier.wosWOS:000287419900076en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBispectral analysisen_US
dc.subjectObstructive sleep apnea syndrome: bicoherenceen_US
dc.subjectQuadratic phase couplingen_US
dc.subjectEEG signalsen_US
dc.subjectArtificial neural networken_US
dc.titleA new approach for estimation of obstructive sleep apnea syndromeen_US
dc.typeArticleen_US

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