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dc.contributor.authorUcar, Muhammed Kursad
dc.contributor.authorBozkurt, Mehmet Recep
dc.contributor.authorPolat, Kemal
dc.contributor.authorBilgin, Cahit
dc.date.accessioned2021-06-23T19:42:23Z
dc.date.available2021-06-23T19:42:23Z
dc.date.issued2015
dc.identifier.isbn978-1-4673-7386-9
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/20.500.12491/8466
dc.description23nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEYen_US
dc.descriptionWOS:000380500900010en_US
dc.description.abstractObstructive Sleep Apnea Syndrome is one of the major diseases of our century. Diagnosis of this disease is very difficult. The reason of the difficulty is the complexity of the system. AHI index is calculated for the diagnosis of the disease as a result of respiratory scoring process. However it is necessary to use four different signals to do this operation. The reduction of signal measurements that discomforts the patient or using different signal measurements will provide the patient to sleep closer to his/her natural sleep environment which will increase the accuracy rate of the studies that are made in literature. Changes occurring in photoplethysmography signal during respiratory events were examined. In this study, the patient data that was used respiratory events were scored Changes on the photoplethysmography signals were examined. The data that were used in this study were respiratory events tagged apnea and hypopnea. For control, the photoplethysmography signals were recorded during normal breathing in sleep. The data were analyzed using the one-way analysis of variance method. According to the obtained results, the photoplethysmography signals have significant changes in between the apnea-hypopnea classes and normal classes during respiratory pauses in sleep. However, there are not significant differences between apnea and hypopnea classes. The study concluded that, in the scoring of respiratory events, photoplethysmography could be used more efficiently using a computer software.en_US
dc.description.sponsorshipDept Comp Engn & Elect & Elect Engn, Elect & Elect Engn, Bilkent Univen_US
dc.language.isoturen_US
dc.publisherIeeeen_US
dc.relation.ispartofseriesSignal Processing and Communications Applications Conference
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectOSASen_US
dc.subjectPhotoplethysmographyen_US
dc.subjectANOVAen_US
dc.titleInvestigation of Effects of Time Domain Features of the Photoplethysmography (PPG) Signal on Sleep Respiratory Arrestsen_US
dc.typeconferenceObjecten_US
dc.contributor.department[0-Belirlenecek]en_US
dc.contributor.authorID0000-0002-0636-8645en_US
dc.contributor.authorID0000-0003-2213-5881en_US
dc.contributor.institutionauthor[0-Belirlenecek]
dc.identifier.startpage124en_US
dc.identifier.endpage127en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.journal2015 23Rd Signal Processing And Communications Applications Conference (Siu)en_US


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