Comparison of Heart Rhythm and Morphological ECG Features in Recognition of Sleep Apnea from the ECG

This study addresses the problem of sleep apnea recognition on a minute-by-minute basis from single-lead ECGs recorded overnight. Analysis of heart rate fluctuations, quantified by the series of RR-intervals, is compared to analysis of ECG morphology variations, assessed using signal vectors from the QRSand the T-wave region and projecting them onto their first principal component. The resulting series of scalar Karhunen–Loève coefficients (KLCs) were used as descriptors of morphology. From the derived series, we calculated a measure of similarity and a spectral index in temporal segments of 5 min, and assessed their diagnostic accuracy by ROCanalysis. Although the performance for the RR-series and the similarity feature was 81% / 84% sens ./ spec., better results up to 87% / 87% were obtained from the T-wave KLCs. It is concluded that the effects of sleep apnea on the ECG are reflected more uniformly in morphology variations of the ECG compared to heart rhythm.