Comparison of heart rate variability (HRV) and nasal pressure in obstructive sleep apnea (OSA) patients during sleep apnea

In this study, a novel R wave detection algorithm was developed and used to analyze the heart rate variability (HRV) of obstructive sleep apnea patients with obstructive sleep apnea (OSA). The purpose of our study was to investigate the biosignal changes in the synchronization between HRV, nasal pressure, and the effect of OSA. HRV, nasal pressure, and sleep electroencephalogram (EEG) signals recorded in control and OSA patients with sleep apnea who were matched according to EEG arousal in OSA during sleep apnea. Experiment steps were completed for R–R interval calculation and to estimate its power spectral density (PSD) over several frequency ranges of apnea states (severe, moderate and mild). Patients with severe OSA had persistently longer R–R intervals compared to patients with mild OSA. As a measure of apnea classification accuracy, the algorithm correctly classified 99.7% of the evaluation database. An advantage of the proposed method is the combination of R wave detection techniques to enhance the accuracy of wave detection that is easily implemented with HRV verified by accurate classification and quantification.

► A novel R wave detection algorithm was developed.
► Used to analyze the HRV of obstructive sleep apnea (OSA) patients with OSA.
► Severe OSA had persistently longer R–R intervals compared to patients with mild OSA.
► Easily implemented with HRV verified by accurate classification and quantification.
► Will help clarify the relationship between cardiovascular disease and sleep apnea.