Summary
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.
Keywords
ECG - ECG-derived respiration - heart rate - respiratory myogram interference - sleep
related breathing disorders
