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:: Volume 28, Issue 6 (Scientific Journal of Kurdistan University of Medical Sciences 2024) ::
SJKU 2024, 28(6): 12-22 Back to browse issues page
Identification of the Ectopic Foci of Focal Atrial Tachycardia (FAT) by Using Electrocardiogram (ECG) Signal Analysis
Fatemeh Mohammadi 1, Ali Sheikhani2 , Farbod Razzazi3 , Alireza Ghorbani Sharif4
1- Department of Medical Sciences and Technologies, Science and Research Branch, Islamic Azad University, Tehran, Iran , fateme.mohammadi86@gmail.com
2- Department of Medical Sciences and Technologies, Science and Research Branch, Islamic Azad University, Tehran, Iran.,
3- Department of Medical Sciences and Technologies, Science and Research Branch, Islamic Azad University, Tehran, Iran
4- Cardiologist Interventional Electrophysiologist of The Arrhythmia Center, Tehran, Iran
Abstract:   (386 Views)
Background and Aim: Cardiac electrophysiology study (EPS) is the study of the electrical system of the heart. One of the most common methods of treating cardiac arrhythmias is ablation. The main problem with this method is determination of the position of the heart that must be be ablated. Electrocardiogram (ECG) signal is used as a non-invasive, safe and fast tool to understand the electrical activity of the heart. The aim of this study was to identify the focal atrial tachycardia ectopic foci based on ECG signal analysis using sparse decomposition algorithm.
Materials and Methods: 12-lead ECG signals of 48 patients with focal atrial tachycardia were recorded and stored. After preprocessing the ECG signals, by using Pan-Tompkins algorithm, each pulse of each signal was separated. Sparse coefficients of test data were calculated based on the sparse decomposition algorithm and the test data were classified. 4 anatomical position in the right atrium, one in the septum and 4 anatomical position in the left atrium were considered as 9 classes and the position of the ectopic foci in each test data was determined.
Results: At first, the location of the ectopic foci was identified in the right or left atrium, and then the exact anatomical position in each atrium was estimated. The average accuracy of identifying the position of ectopic foci in 5 runs of algorithm was 81.27±2.78. The mean accuracy of identification of ectopic foci was 61.73% in 4 anatomical position of right atrium, 64.05% in septum and 65.16% in 4 anatomical position of left atrium.
Conclusion: Based on the findings of the study, the location of the ectopic foci of focal atrial tachycardia can be identified with appropriate accuracy using ECG signal analysis before performing electrophysiological study.

 
Keywords: Heart electrophysiology, Ablation, Focal atrial tachycardia (FAT), Sparse decomposition algorithm.
Full-Text [PDF 959 kb]   (84 Downloads)    
Type of Study: Original Research | Subject: Medicine - Cardiovascular
Received: 2021/09/20 | Accepted: 2022/08/16 | Published: 2024/02/6
References
1. Fogoros R. Electrophysiologic Testing. Tehran: Mirmah Publication. Tehran arrhythmia Center. 3rd ed. 1998;5-17. ISBN: 9789648115130.
2. Eslami M, Bagherzadeh A. Fundamentals of Cardiac Electrophysiology. Tehran: Iran Behdasht publication. 2010. ISBN: 9789640466179.
3. Kistler P M, Roberts-Thomson K C, Haqqani H M, Fynn S P. P-wave morphology in focal atrial tachycardia: development of an algorithm to predict the anatomic site of origin. Journal of the American College of Cardiology (JACC). 2006;48(5):1010-1017. [DOI:10.1016/j.jacc.2006.03.058] [PMID]
4. Teh A W, Kistler P M, Kalman J M. Using the 12‐Lead ECG to Localize the Origin of Ventricular and Atrial Tachycardias: Part 1. Focal Atrial Tachycardia: CME. Journal of cardiovascular electrophysiology (JCardioEP), 2009;20(6):706-709. [DOI:10.1111/j.1540-8167.2009.01456.x] [PMID]
5. Shah A J, Lim H S, Yamashita S, Zellerhoff S, Berte B, et. Al. Non-invasive ECG mapping to guide catheter ablation. Journal of atrial fibrillation (JAFIB). 2014;7(3): 31-38.
6. Alday E A P, Colman M A, Langley P, Butters T D, et. al. A New Algorithm to Diagnose Atrial Ectopic Origin from Multi Lead ECG Systems - Insights from 3D Virtual Human Atria and Torso. PLOS Computational Biology (PLOS Comput. Biol). 2015;11(1):1-15. [DOI:10.1371/journal.pcbi.1004026] [PMID] []
7. MS Lee J, P Fynn S. P wave morphology in guiding the ablation strategy of focal atrial tachycardias and atrial flutter. Current cardiology reviews. 2015;11(2):103-110. [DOI:10.2174/1573403X10666141013121252] [PMID] []
8. Provost J, Costet A, Wan E, Gambhir A, Whang, et. al. Assessing the atrial electromechanical coupling during atrial focal tachycardia, flutter, and fibrillation using electromechanical wave imaging in humans, Computers in biology and medicine. 2015; 65:161-167. [DOI:10.1016/j.compbiomed.2015.08.005] [PMID] []
9. Ramanathan C, Ghanem R N, Jia P, et. al. Noninvasive electrocardiographic imaging for cardiac electrophysiology and arrhythmia. Nature medicine. 2004;10(4):422-428. [DOI:10.1038/nm1011] [PMID] []
10. Uhm J S, Shim J, Wi J, Mun H S, Pak H N, Lee M, et. al. An electrocardiography algorithm combined with clinical features could localize the origins of focal atrial tachycardias in adjacent structures. Europace (EP). 2014;16(7):1061-1068. [DOI:10.1093/europace/eut393] [PMID]
11. Pan, J, Tompkins W J. A real-time QRS detection algorithm. IEEE Trans. Biomed. Eng. 1985;32(3): 230-236. [DOI:10.1109/TBME.1985.325532] [PMID]
12. Debnath, T, Hasan M, Biswas T. Analysis of ECG signal and classification of heart abnormalities using Artificial Neural Network. In 2016 9th International Conference on Electrical and Computer Engineering (ICECE). 2016;353-356. [DOI:10.1109/ICECE.2016.7853929] [PMID] []
13. Mallat S G, & Zhang Z. Matching pursuits with time-frequency dictionaries. IEEE Trans. Signal Process. 1993;41(12): 3397-3415. [DOI:10.1109/78.258082]
14. Figueiredo M A, Nowak R D, Wright S J. Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems. IEEE JSTSP. 2007;1(4):586-597. [DOI:10.1109/JSTSP.2007.910281]
15. Shayestenia N, keshavarz A, Rostami H. Investigation of Gradient Image Algorithm for Sparse Reconstruction (GPSR). Conference on Computer Engineering and Sustainable Development with a focus on computer networks, modeling and systems security, Mashhad, Iran. 2013;121-129.
16. Yang J, Peng Y, Xu W, Dai Q. Ways to sparse representation: an overview. Science China Information Sciences. 2009; 52(4):695-703. [DOI:10.1007/s11432-009-0045-5]
17. Rodriguez F, Sapiro G. Sparse representations for image classification: Learning discriminative and reconstructive non-parametric dictionaries, IMA Preprint Series # 2213, University of Minnesota, 2008;612-626. [DOI:10.21236/ADA513220]
18. Wright J, Yang A Y, Ganesh A, Sastry S, Ma Y. Robust face recognition via sparse representation. IEEE transactions on pattern analysis and machine intelligence. 2008;31(2):210-227. [DOI:10.1109/TPAMI.2008.79] [PMID]
19. Mohammadi F, Sheikhani A, Razzazi F, & Ghorbani sharif A. Non-Invasive Localization of the Ectopic Foci of Focal Atrial Tachycardia by Using ECG Signal based Sparse Decomposition Algorithm. Journal of Biomedical Signal Processing and Control. 2021;70:1-10. [DOI:10.1016/j.bspc.2021.103014]
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Mohammadi F, Sheikhani A, Razzazi F, Ghorbani Sharif A. Identification of the Ectopic Foci of Focal Atrial Tachycardia (FAT) by Using Electrocardiogram (ECG) Signal Analysis. SJKU 2024; 28 (6) :12-22
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Volume 28, Issue 6 (Scientific Journal of Kurdistan University of Medical Sciences 2024) Back to browse issues page
مجله علمی دانشگاه علوم پزشکی کردستان Scientific Journal of Kurdistan University of Medical Sciences
مجله علمی دانشگاه علوم پزشکی کردستان Scientific Journal of Kurdistan University of Medical Sciences
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