Akademik Veri Yönetim Sistemi
27th Signal Processing and Communications Applications Conference (SIU), Sivas, Türkiye, 24 - 26 Nisan 2019
Polysomnography (PSG) is the principle method for diagnosis of sleep disorder and sleep breathing disorders (SDB). Developments in technology makes it possible to develop the diagnostic tools smaller in size, lesser in cost and easier to use which can be used for diagnosis of sleep disorders and sleep breathing disorders at home environment instead of hospitals. In this study, a previously developed Level-3 PSG device is used for pre-diagnosis of sleep breathing disorder and some physiological data are acquired and using Pan&Tompkins Algorithm, parameters such as QRS complex and Hearth Rate Variablity (HRV) are derived as they have been found important for the diagnosis. Data acquired from 5 patients in parallel manner using both the device developed and the Level-1 PSG device which is considered golden standard in diagnosis of SDB in hospital environment. Data that acquired jointly are examined and their cross-correlation index was found to be 0.906. In addition, the cross-correlation index was calculated between signals from the device developed and Level-1 PSG by applying Pan&Tompkins Algorithm to respiration signals and it was found to be 0.9354. With this study, the quantitative diagnostic capability of portable devices based on the signals acquired both from the portable device and PSG, it is found that suitable to make a diagnostic reasoning over these limited recorded data. In order for the portable devices to be used in the diagnosis stage as a standard, more tests should be performed on more data sets.