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dc.contributor.authorErdamar, Aykut
dc.contributor.authorBayrak, Tuncay
dc.contributor.authorFirat, Hikmet
dc.contributor.authorMutlu, Murad
dc.contributor.authorArdic, Sadik
dc.contributor.authorEroglu, Osman
dc.date.accessioned2019-06-10T19:36:34Z
dc.date.available2019-06-10T19:36:34Z
dc.date.issued2017
dc.identifier.issn2148-1504
dc.identifier.urihttp://cms.galenos.com.tr/Uploads/Article_16002/6-15.pdf
dc.identifier.urihttp://hdl.handle.net/11727/3431
dc.description.abstractObjective: In this work, a new methodology based on signal processing techniques for the quantitative analysis of uvulopalatal flap surgery is proposed. Clinical assessment studies of uvulopalatal flap surgery are based on not only the physician's examination, but also the patient's subjective feedback. Quantitative and objective evaluation studies are still lacking in the literature. Materials and Methods: Full night sleep records were analyzed for 21 patients before and after the surgery. The proposed algorithm consists of two independent parts. In the first part, the heart rate variability and complexity of the electrocardiogram were calculated. The second part includes calculating the electroencephalogram sub-band energy. Afterwards, the statistical methods were applied in order to determine the correlation of clinical and experimental parameters. Results: The low frequency/high frequency ratio and the sub-band energy of beta wave were significant for the patients having low postoperative delta sleep duration. Moreover, the sub-band energies of both alpha and beta waves, and theta wave were significant for the patients who had high post-operative delta sleep duration and blood oxygen saturation (SaO(2))-parameter. Complexity was significant for the patients with low postoperative respiratory disturbance index and SaO(2) parameter, and respiratory disturbance is correlated with snoring index. Conclusion: Respiratory disturbance index, which is not significant according to the pre- and post-operative clinical findings, was found to be directly related to the complexity feature. The most important result of this work is that the pre-operative complexity feature is correlated with respiratory disturbance and snoring index. This means that complexity feature can be a predictor prior to surgery.en_US
dc.language.isoengen_US
dc.relation.isversionof10.4274/jtsm.21931en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectSleep disordersen_US
dc.subjectObstructive sleep apneaen_US
dc.subjectUvulopalatal flap surgeryen_US
dc.subjectComplexityen_US
dc.subjectHjorth parametersen_US
dc.titleThe Quantitative Analysis of Uvulopalatal Flap Surgeryen_US
dc.typearticleen_US
dc.relation.journalJOURNAL OF TURKISH SLEEP MEDICINE-TURK UYKU TBB DERGISIen_US
dc.identifier.volume4en_US
dc.identifier.issue1en_US
dc.identifier.startpage6en_US
dc.identifier.endpage15en_US
dc.identifier.wos000410796000003en_US
dc.contributor.orcID0000-0001-8588-480Xen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergien_US
dc.contributor.researcherIDAAA-6844-2019en_US


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