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- W1499340917 abstract "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." @default.
- W1499340917 created "2016-06-24" @default.
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- W1499340917 date "2014-01-01" @default.
- W1499340917 modified "2023-09-26" @default.
- W1499340917 title "Robust Detection of Sleep Apnea from Holter ECGs" @default.
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- W1499340917 doi "https://doi.org/10.3414/me13-02-0043" @default.
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