Detection of the electrode disconnection in sleep signals [Uyku Sinyallerindeki Elektrod Kopuklu?unun Tespit Edilmesi]

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dc.contributor.authorYücelbaş C.
dc.contributor.authorÖzşen S.
dc.contributor.authorYücelbaş S.
dc.contributor.authorTezel G.
dc.contributor.authorDursun M.
dc.contributor.authorYosunkaya S.
dc.contributor.authorKüççüktürk S.
dc.date.accessioned2020-03-26T19:08:03Z
dc.date.available2020-03-26T19:08:03Z
dc.date.issued2015
dc.departmentSelçuk Üniversitesien_US
dc.description2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 -- 16 May 2015 through 19 May 2015 -- 113052en_US
dc.description.abstractSleep staging process that is performed in sleep laboratories in hospitals has an important role in diagnosing some of the sleep disorders and disturbances which are seen in sleep. And also it is an indispensable method. It is usually performed by a sleep expert through examining during the night of the patients (6-8 hours) recorded Electroencephalogram (EEG), Electrooculogram (EOG), Electromyogram (EMG), electrocardiogram (ECG) and other some 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 studies has come to the fore. However, none of the so far made automatic sleep staging was not accepted by the experts. The most important reason is that the results of the automated systems are not desired accuracy. There are many factors that affecting the accuracy of the systems, such as noise, the inter-channel interference, excessive body movements and disconnection of electrodes. In this study, we examined the written an algorithm to be able to determine to what extent the disconnection of electrodes in EEG signal that obtained one healthy person at the sleep laboratory of Meram Medicine Faculty of Necmettin Erbakan University. According to the obtained application results, the electrodes disconnection in EEG signal could be detected maximum of 100% and minimum of 99.12% accuracy. Accordingly, based on the success achieved in the study, this algorithm is thought to contribute positively to the researchers that the work on and will work on sleep staging problems and increase the success of automatic sleep staging systems. © 2015 IEEE.en_US
dc.identifier.doi10.1109/SIU.2015.7129824en_US
dc.identifier.endpage326en_US
dc.identifier.isbn9.78147E+12
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage323en_US
dc.identifier.urihttps://dx.doi.org/10.1109/SIU.2015.7129824
dc.identifier.urihttps://hdl.handle.net/20.500.12395/32767
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 - Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectEEGen_US
dc.subjectelectrode disconnectionen_US
dc.subjectsleep stagingen_US
dc.titleDetection of the electrode disconnection in sleep signals [Uyku Sinyallerindeki Elektrod Kopuklu?unun Tespit Edilmesi]en_US
dc.typeConference Objecten_US

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