Kaya, YilmazSezgin, NecmettinErtugrul, Omer Faruk2024-12-242024-12-242017978-1-5386-1880-6https://hdl.handle.net/20.500.12604/57452017 International Artificial Intelligence and Data Processing Symposium (IDAP) -- SEP 16-17, 2017 -- Malatya, TURKEYIn this study, a new approach for estimation of Obstructive Sleep Apnea Syndrome (OSAS) was proposed. OSAS is a sleep disorder that affects the life comfortability in human life. Diagnosis of OSAS is usually done by expensive devices and specialist physicians. Since OSAS is serious, it should be diagnosed and treated early. In this study, a new feature extraction method is proposed for OSAS diagnosis from snoring signals. With one (1) dimensional ternary pattern method, effective attributes were extracted from raw snoring signals and identification process was performed by classification methods. According to the obtained results, 1D-TP method has shown significant success in diagnosing OSAS from snore signals. The results can be used in sleep laboratory for help to experts before put patient to the Polysomnography (PSG) test.trinfo:eu-repo/semantics/closedAccessternary patternsclassificationfeatures extractionObstructive sleep apnea syndromeConference ObjectN/AWOS:000426868700173N/A2-s2.0-85039913873