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...
Gespeichert in:
| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2 August 2014
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| In: |
Journal of electrocardiology
Year: 2014, Jahrgang: 47, Heft: 6, Pages: 826-830 |
| ISSN: | 1532-8430 |
| DOI: | 10.1016/j.jelectrocard.2014.07.017 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.jelectrocard.2014.07.017
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| Verfasserangaben: | Christoph Maier, Hartmut Dickhaus |
MARC
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| 245 | 1 | 0 | |a Extraction of respiratory myogram interference from the ECG and its application to characterize sleep-related breathing disorders in atrial fibrillation |c Christoph Maier, Hartmut Dickhaus |
| 264 | 1 | |c 2 August 2014 | |
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| 520 | |a 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. | ||
| 650 | 4 | |a Aged | |
| 650 | 4 | |a Algorithms | |
| 650 | 4 | |a Artifacts | |
| 650 | 4 | |a Atrial fibrillation | |
| 650 | 4 | |a Atrial Fibrillation | |
| 650 | 4 | |a Diagnosis, Computer-Assisted | |
| 650 | 4 | |a ECG | |
| 650 | 4 | |a ECG-derived respiration | |
| 650 | 4 | |a Electrocardiography | |
| 650 | 4 | |a Female | |
| 650 | 4 | |a Humans | |
| 650 | 4 | |a Male | |
| 650 | 4 | |a Middle Aged | |
| 650 | 4 | |a Pattern Recognition, Automated | |
| 650 | 4 | |a QRS amplitude | |
| 650 | 4 | |a Reproducibility of Results | |
| 650 | 4 | |a Respiratory Mechanics | |
| 650 | 4 | |a Respiratory myogram interference | |
| 650 | 4 | |a Sensitivity and Specificity | |
| 650 | 4 | |a Sleep apnea | |
| 650 | 4 | |a Sleep Apnea Syndromes | |
| 650 | 4 | |a Sleep-related breathing disorders | |
| 650 | 4 | |a Supraventricular arrhythmia | |
| 700 | 1 | |a Dickhaus, Hartmut |e VerfasserIn |0 (DE-588)172054710 |0 (DE-627)696958074 |0 (DE-576)132929090 |4 aut | |
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