The importance of the very low frequency power of heart rate variability in screening of patients with obstructive sleep Apnea

Sleep apnea is a complete or partial cessation of breathing during sleep. Obstructive sleep Apnea (OSA) is the common form of apnea that occurs when the upper airway is partially or completely obstructed due to the relaxation of dilating muscles. In developed countries the cost of investigating patients has increased considerably during the last decade as the only reliable method for the diagnosis of OSA until now is overnight sleep studies (Polysomnography), which is a cumbersome, time consuming and expensive procedure requiring specially trained polysomnographers and needs recording of ECG, EEG, EMG, EOG, nasal air respiratory effort and oxygen saturation. Therefore, it is of great importance and interest to have automatic screening algorithms on a single lead ECG signals. This will reduce the pressure on sleep laboratories and make it possible to diagnose sleep apnea inexpensively from ECG recordings acquired easily in the patient´s home. The instantaneous heart rate is measured as the time in seconds between peaks of two consecutive R waves of the ECG signal. This time is referred to as RRI. The frequency spectrum of the RRI data is divided into three main bands: VLF (0.0033-0.04 Hz), LF (0.04-0.15 Hz), and HF (0.15-0.4 Hz). In this work, the spectral of the RRI is obtained by using a soft decision wavelet decomposition algorithm (SDWDA) for the purpose of screening of patients with OSA. The power entropy ratios of the three frequency bands are used as identification factors. The efficiency of classification of MIT trial data is obtained and a threshold between the two groups have been set in order to be used in the next step to evaluate the MIT-test data. The result shows the importance of the VLF band compared to the HF band, which has been used with the LF band in many studies for screening of patients with OSA