AN IMPROVED APPROACH FOR REAL-TIME DETECTION OF SLEEP APNEA

The traditional diagnosis of sleep apnea and hypopnea syndrome (SANS) requires an expensive and complex overnight procedure called polysomnography (PSG). Recently, finding valid alternatives for SAHS diagnosis has attracted much research attention. This paper focuses on the real-time monitoring and detection of SAHS based on the arterial oxygen saturation signal measured by pulse oximetry (SpO(2)). We develop a more comprehensive feature set and a more appropriate annotation criterion, if compared to the existing approaches in the literature. To enjoy competitiveness in computational complexity, we also propose a reduced feature set which provides a higher sensitivity and better adaptivity to distinct databases. The performances of 15 commonly used classifiers with different cost matrixes are assessed on different databases, offering detailed insights on the diagnostic abilities of these methods.