Abstract
Pulse rate variability (PRV), an alternative measure of heart rate variability (HRV), is altered during obstructive sleep apnea. Correntropy spectral density (CSD) is a novel spectral analysis that includes nonlinear information. We recruited 160 children and recorded SpO2 and photoplethysmography (PPG), alongside standard polysomnography. PPG signals were divided into 1-min epochs and apnea/hypoapnea (A/H) epochs labeled. CSD was applied to the pulse-to-pulse interval time series (PPIs) and five features extracted: the total spectral power (TP: 0.01–0.6 Hz), the power in the very low frequency band (VLF: 0.01–0.04 Hz), the normalized power in the low and high frequency bands (LFn: 0.04–0.15 Hz, HFn: 0.15–0.6 Hz), and the LF/HF ratio. Nonlinearity was assessed with the surrogate data technique. Multivariate logistic regression models were developed for CSD and power spectral density (PSD) analysis to detect epochs with A/H events. The CSD-based features and model identified epochs with and without A/H events more accurately relative to PSD-based analysis (area under the curve (AUC) 0.72 vs. 0.67) due to the nonlinearity of the data. In conclusion, CSD-based PRV analysis provided enhanced performance in detecting A/H epochs, however, a combination with overnight SpO2 analysis is suggested for optimal results.
Highlights
Obstructive sleep apnea (OSA), the most common form of sleep-disordered breathing, is characterized by the obstruction of the upper airway, which disrupts normal breathing during sleep
We investigated the effect of OSA on sympathetic and parasympathetic activity, applying Correntropy spectral density (CSD) to the pulse-to-pulse intervals of the PPG signal recorded with the Phone Oximeter
Using the scores performed by the sleep technician based on the polysomnography study, all epochs were labelled as OSA epochs if they contained A/H events or non-OSA events if they did not
Summary
Obstructive sleep apnea (OSA), the most common form of sleep-disordered breathing, is characterized by the obstruction of the upper airway, which disrupts normal breathing during sleep. The prevalence of OSA ranges from 0.1% to 13% [1]; and can result in severe complications if untreated, such as: heart failure, developmental delay, and growth and behavioural problems [2]. The gold standard for OSA diagnosis, polysomnography, is resource intensive and not widely available. Overnight oximetry has been studied as a potential standalone method to diagnose OSA. We showed that characterization of oxygen saturation recorded by the Phone Oximeter (a smartphone-based pulse oximeter) could identify children with OSA [3]. We observed some sleep apnea events that occurred in the absence of oxygen desaturation
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