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Extraction of respiratory myogram interference from the ECG and its application to characterize sleep-related breathing disorders in atrial fibrillation

BACKGROUND AND PURPOSE: Present methods to extract respiratory myogram interference (RMI) from the Holter-ECG and assess effect of supraventricular arrhythmias (SVAs) onto ECG-based detection of sleep-related breathing disorders (SRBDs) and AHI estimation. - METHODS: RMI was quantified as residual e...

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Bibliographic Details
Main Authors: Maier, Christoph (Author) , Dickhaus, Hartmut (Author)
Format: Article (Journal)
Language:English
Published: 2 August 2014
In: Journal of electrocardiology
Year: 2014, Volume: 47, Issue: 6, Pages: 826-830
ISSN:1532-8430
DOI:10.1016/j.jelectrocard.2014.07.017
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.jelectrocard.2014.07.017
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Author Notes:Christoph Maier, Hartmut Dickhaus
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Summary:BACKGROUND AND PURPOSE: Present methods to extract respiratory myogram interference (RMI) from the Holter-ECG and assess effect of supraventricular arrhythmias (SVAs) onto ECG-based detection of sleep-related breathing disorders (SRBDs) and AHI estimation. - METHODS: RMI was quantified as residual energy after ECG cancellation or high-pass filtering for different windowing constellations. In 140 cases without (SET_A) and 10 cases with persistent SVAs (SET_B), respiratory polysomnogram annotations served as reference for SRDB detection from Holter-ECGs. We applied our previously published method to identify SRDBs in 1-min epochs and estimate the AHI based on joint modulations in RMI and QRS-area. - RESULTS: Sensitivity and specificity of 0.855/0.860 in SET_A dropped to 0.831/0.75 in SET_B. A significantly higher number of wake events in SET_B likely contribute to the asymmetric decrease and is consistent with a tendency to overestimate the AHI. - CONCLUSIONS: Despite reduced accuracy, RMI and QRS-area appear relatively robust against SVA and promise Holter-based detection at least of medium to severe SRBDs also in patients with SVAs.
Item Description:Gesehen am 18.12.2020
Physical Description:Online Resource
ISSN:1532-8430
DOI:10.1016/j.jelectrocard.2014.07.017

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