Robust detection of sleep apnea from Holter ECGs. Joint assessment of modulations in QRS amplitude and respiratory myogram interference.

INTRODUCTION This article is part of the Focus Theme of Methods of Information in Medicine on "Biosignal Interpretation: Advanced Methods for Studying Cardiovascular and Respiratory Systems". OBJECTIVES Detect presence of sleep-related breathing disorders (SRBD) in epochs of 1 min by signal analysis of Holter ECG recordings. METHODS In 121 patients, 140 synchronized polysomnograms (PSGs) and 8-channel Holter ECGs were recorded. The only excluded condition was persistent arrhythmias. Respiratory events as scored from the PSGs were mapped to a 1 min grid and served as reference for ECG-based detection. Moreover, 69/70 recordings of the Physionet Sleep Apnea ECG Database (PADB) were included. We performed receiver operating characteristics analysis of a single, novel time-domain feature, the joint local similarity index (jLSI). Based on cross-correlation, the jLSI quantifies the time-locked occurrence of characteristic low-frequency (LF) modulations in ECG respiratory myogram interference (RMI), QRS amplitude (QRSA) and heart rate. RESULTS Joint oscillations in QRSA, RMI and the envelope of RMI identified positive epochs with a sensitivity of 0.855 (PADB: 0.873) and a specificity of 0.86 (PADB: 0.88). Inclusion of heart rate did not improve detection accuracy. CONCLUSIONS Joint occurrence of LF-modulations in QRSA and RMI is a characteristic feature of SRBD that is robustly quantified by the jLSI and permits reliable and reproducible detection of sleep apnea in very heterogeneous settings.