A Novel Approach to Diagnosis of Sleep Apnea from Snoring Signals: Ternary Pattern Method
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Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
In 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.
Description
2017 International Artificial Intelligence and Data Processing Symposium (IDAP) -- SEP 16-17, 2017 -- Malatya, TURKEY
Keywords
ternary patterns, classification, features extraction, Obstructive sleep apnea syndrome
Journal or Series
2017 International Artificial Intelligence and Data Processing Symposium (Idap)
WoS Q Value
N/A
Scopus Q Value
N/A
