EFFECT OF SOME POWER SPECTRAL DENSITY ESTIMATION METHODS ON AUTOMATIC SLEEP STAGE SCORING USING ARTIFICIAL NEURAL NETWORKS

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dc.contributor.authorYucelbas, Cuneyt
dc.contributor.authorOzsen, Seral
dc.contributor.authorGunes, Salih
dc.contributor.authorYosunkaya, Sebnem
dc.date.accessioned2024-02-23T14:45:44Z
dc.date.available2024-02-23T14:45:44Z
dc.date.issued2013
dc.departmentNEÜen_US
dc.description.abstractSleep staging has an important role in diagnosing sleep disorders. It is usually done by a sleep expert through examining sleep Electroencephalogram (EEG), Electrooculogram (EOG), Electromyogram (EMG) signals of the patients and determining the stages of sleep in different time sections named as epochs. Manual sleep staging is preferred among the sleep experts but because it is rather tiring and time consuming task, automatic sleep stage scoring systems get popularity. In this study, we obtained EEG, EMG and EOG signals of four healthy people at sleep laboratory of Meram Medicine Faculty of Necmettin Erbakan University to use them in sleep staging and extracted 20 different features by using some power spectral density estimation methods which are: Fast Fourier Transform (FFT), Welch and Autoregressive (AR). We evaluated the effects of these methods on sleep staging through using ANN classifier. Comparison between these methods was done on each individual whose data were utilized separately from others. According to the results, the maximum test classification accuracy was reported as 79.72% by using of FFT method for subject1. Also, mean of test classification accuracies for all of subjects were obtained as 74.14%, 71,58 and 70.34% with use of FFT, Welch and AR, respectively.en_US
dc.description.sponsorshipScientific Research Projects of Selcuk Universityen_US
dc.description.sponsorshipThis study is supported by the Scientific Research Projects of Selcuk University.en_US
dc.identifier.endpage131en_US
dc.identifier.issn1646-3692
dc.identifier.issue2en_US
dc.identifier.startpage119en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12452/17600
dc.identifier.volume8en_US
dc.identifier.wosWOS:000451323400010en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherIadisen_US
dc.relation.ispartofIadis-International Journal On Computer Science And Information Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial Neural Networksen_US
dc.subjectAutomatic Sleep Stageen_US
dc.subjectEegen_US
dc.subjectPsden_US
dc.titleEFFECT OF SOME POWER SPECTRAL DENSITY ESTIMATION METHODS ON AUTOMATIC SLEEP STAGE SCORING USING ARTIFICIAL NEURAL NETWORKSen_US
dc.typeArticleen_US

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