Pairwise ANFIS approach to determining the disorder degree of obstructive sleep apnea syndrome

dc.contributor.authorPolat, Kemal
dc.contributor.authorYosunkaya, Sebnem
dc.contributor.authorGunes, Salih
dc.date.accessioned2020-03-26T17:27:24Z
dc.date.available2020-03-26T17:27:24Z
dc.date.issued2008
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractObstructive sleep apnea syndrome (OSAS) is an important disease that affects both the right and the left cardiac ventricle. This paper presents a novel classification method called pairwise ANFIS based on Adaptive Neuro-Fuzzy Inference System (ANFIS) and one against all method for detecting the obstructive sleep apnea syndrome. In order to extract the features related with OSAS, we have used the clinical features obtained from Polysomnography device as a diagnostic tool for obstructive sleep apnea (OSA) in patients clinically suspected of suffering from this disease. The clinical features obtained from Polysomnography Reports are Arousals Index (ARI), Apnea and Hypoapnea Index (AHI), SaO(2) minimum value in stage of REM, and Percent Sleep Time (PST) in stage of SaO(2) intervals bigger than 89%. Since ANFIS has output with one class, we have extended the output of ANFIS to multi class by means of one against all method to diagnose the OSAS that has four classes consisting of normal (25 subjects), mild OSAS (AHI=5-15 and 14 subjects), middle OSAS (AHI < 15-30 and 18 subjects), and heavy OSAS (AHI > 30 and 26 subjects). The classification accuracy, sensitivity and specifity analysis, mean square error, and confusion matrix have been used to test the performance of proposed method. The obtained classification accuracies are 82.92%, 82.92%, 85.36%, and 87.80% for each class including normal, mild OSAS, middle OSAS, and heavy OSAS using ANFIS with one against all method with 50-50% train-test split, respectively. Combining ANFIS and one against all method that is firstly proposed by us was firstly applied for diagnosing the OSAS. The proposed method has produced very promising results in the detecting the obstructive sleep apnea syndrome.en_US
dc.description.sponsorshipSelcuk UniversitySelcuk Universityen_US
dc.description.sponsorshipThis study has been supported by Scientific Research Project of Selcuk University.en_US
dc.identifier.doi10.1007/s10916-008-9143-yen_US
dc.identifier.endpage387en_US
dc.identifier.issn0148-5598en_US
dc.identifier.issn1573-689Xen_US
dc.identifier.issue5en_US
dc.identifier.pmid18814494en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage379en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s10916-008-9143-y
dc.identifier.urihttps://hdl.handle.net/20.500.12395/22555
dc.identifier.volume32en_US
dc.identifier.wosWOS:000258932600003en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherSPRINGERen_US
dc.relation.ispartofJOURNAL OF MEDICAL SYSTEMSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectobstructive sleep apnea syndrome (OSAS)en_US
dc.subjectadaptive Neuro-Fuzzy Inference System (ANFIS)en_US
dc.subjectpairwise ANFISen_US
dc.subjectpolysomnographyen_US
dc.titlePairwise ANFIS approach to determining the disorder degree of obstructive sleep apnea syndromeen_US
dc.typeArticleen_US

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