Atrial flutter and atrial tachycardia detection using Bayesian approach with high resolution time-frequency spectrum from ECG recordings
(2013) In Biomedical Signal Processing and Control 8(6). p.992-999- Abstract
- Contemporary methods of atrial flutter (AFL), atrial tachycardia (AT), and atrial fibrillation (AF) monitoring, although superior to the standard 12-lead ECG and symptom-based monitoring, are unable to accurately discriminate between AF, AFL and AT. Thus, there is a need to develop accurate, automated, and comprehensive atrial arrhythmia detection algorithms using standard ECG recorders. To this end, we have developed a sensitive and real-time realizable algorithm for accurate AFL and AT detection using any standard electrocardiographic recording. Our novel method for automatic detection of atrial flutter and atrial tachycardia uses a Bayesian approach followed by a high resolution time-frequency spectrum. We find the TQ interval of the... (More)
- Contemporary methods of atrial flutter (AFL), atrial tachycardia (AT), and atrial fibrillation (AF) monitoring, although superior to the standard 12-lead ECG and symptom-based monitoring, are unable to accurately discriminate between AF, AFL and AT. Thus, there is a need to develop accurate, automated, and comprehensive atrial arrhythmia detection algorithms using standard ECG recorders. To this end, we have developed a sensitive and real-time realizable algorithm for accurate AFL and AT detection using any standard electrocardiographic recording. Our novel method for automatic detection of atrial flutter and atrial tachycardia uses a Bayesian approach followed by a high resolution time-frequency spectrum. We find the TQ interval of the electrocardiogram (ECG) corresponding to atrial activity by using a particle filter (PF), and analyze the atrial activity with a high resolution time-frequency spectral method: variable frequency complex demodulation (VFCDM). The rationale for using a high-resolution time-frequency algorithm is that our approach tracks the time-varying fundamental frequency of atrial activity, where AT is within 2.0-4.0 Hz, AFL is within 4.0-5.3 Hz and NSR is found at frequencies less than 2.0 Hz. For classifications of AFL (n = 22), AT (n = 10) and normal sinus rhythms (NSR) (n = 29), we found that our approach resulted in accuracies of 0.89, 0.87 and 0.91, respectively; the overall accuracy was 0.88. (C) 2013 Elsevier Ltd. All rights reserved. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4319305
- author
- Lee, Jinseok ; McManus, David D. ; Bourrell, Peter ; Sörnmo, Leif LU and Chon, Ki H.
- organization
- publishing date
- 2013
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Atrial flutter, Atrial tachycardia, Particle filter, Dynamic ECG model, High resolution time-frequency spectrum, Variable frequency complex, demodulation, Electrocardiogram
- in
- Biomedical Signal Processing and Control
- volume
- 8
- issue
- 6
- pages
- 992 - 999
- publisher
- Elsevier
- external identifiers
-
- wos:000329885000057
- scopus:84890122582
- ISSN
- 1746-8094
- DOI
- 10.1016/j.bspc.2013.04.002
- language
- English
- LU publication?
- yes
- id
- a1285735-c780-4ae4-8611-f0fa85327af1 (old id 4319305)
- date added to LUP
- 2016-04-01 14:28:56
- date last changed
- 2022-01-28 00:51:50
@article{a1285735-c780-4ae4-8611-f0fa85327af1,
abstract = {{Contemporary methods of atrial flutter (AFL), atrial tachycardia (AT), and atrial fibrillation (AF) monitoring, although superior to the standard 12-lead ECG and symptom-based monitoring, are unable to accurately discriminate between AF, AFL and AT. Thus, there is a need to develop accurate, automated, and comprehensive atrial arrhythmia detection algorithms using standard ECG recorders. To this end, we have developed a sensitive and real-time realizable algorithm for accurate AFL and AT detection using any standard electrocardiographic recording. Our novel method for automatic detection of atrial flutter and atrial tachycardia uses a Bayesian approach followed by a high resolution time-frequency spectrum. We find the TQ interval of the electrocardiogram (ECG) corresponding to atrial activity by using a particle filter (PF), and analyze the atrial activity with a high resolution time-frequency spectral method: variable frequency complex demodulation (VFCDM). The rationale for using a high-resolution time-frequency algorithm is that our approach tracks the time-varying fundamental frequency of atrial activity, where AT is within 2.0-4.0 Hz, AFL is within 4.0-5.3 Hz and NSR is found at frequencies less than 2.0 Hz. For classifications of AFL (n = 22), AT (n = 10) and normal sinus rhythms (NSR) (n = 29), we found that our approach resulted in accuracies of 0.89, 0.87 and 0.91, respectively; the overall accuracy was 0.88. (C) 2013 Elsevier Ltd. All rights reserved.}},
author = {{Lee, Jinseok and McManus, David D. and Bourrell, Peter and Sörnmo, Leif and Chon, Ki H.}},
issn = {{1746-8094}},
keywords = {{Atrial flutter; Atrial tachycardia; Particle filter; Dynamic ECG model; High resolution time-frequency spectrum; Variable frequency complex; demodulation; Electrocardiogram}},
language = {{eng}},
number = {{6}},
pages = {{992--999}},
publisher = {{Elsevier}},
series = {{Biomedical Signal Processing and Control}},
title = {{Atrial flutter and atrial tachycardia detection using Bayesian approach with high resolution time-frequency spectrum from ECG recordings}},
url = {{http://dx.doi.org/10.1016/j.bspc.2013.04.002}},
doi = {{10.1016/j.bspc.2013.04.002}},
volume = {{8}},
year = {{2013}},
}