Automated Atrial Fibrillation Detection by ECG Signal Processing: A Review

Cardiovascular diseases are the main cause of death in the world, according to the World Health Organization. Among them, ischemic heart disease is at the top, followed by a stroke. Several studies have revealed that atrial fibrillation (AF), which is the most common cardiac arrhythmia, increases up...

Full description

Autores:
Giraldo-Guzmán, Jader
Contreras-Ortiz, Sonia H.
Kotas, Marian
Castells, Francisco
Moroń, Tomasz
Tipo de recurso:
Fecha de publicación:
2021
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/12297
Acceso en línea:
https://hdl.handle.net/20.500.12585/12297
Palabra clave:
Atrial Fibrillation;
Supraventricular Premature Beat;
Brain Ischemia
LEMB
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
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repository_id_str
dc.title.spa.fl_str_mv Automated Atrial Fibrillation Detection by ECG Signal Processing: A Review
title Automated Atrial Fibrillation Detection by ECG Signal Processing: A Review
spellingShingle Automated Atrial Fibrillation Detection by ECG Signal Processing: A Review
Atrial Fibrillation;
Supraventricular Premature Beat;
Brain Ischemia
LEMB
title_short Automated Atrial Fibrillation Detection by ECG Signal Processing: A Review
title_full Automated Atrial Fibrillation Detection by ECG Signal Processing: A Review
title_fullStr Automated Atrial Fibrillation Detection by ECG Signal Processing: A Review
title_full_unstemmed Automated Atrial Fibrillation Detection by ECG Signal Processing: A Review
title_sort Automated Atrial Fibrillation Detection by ECG Signal Processing: A Review
dc.creator.fl_str_mv Giraldo-Guzmán, Jader
Contreras-Ortiz, Sonia H.
Kotas, Marian
Castells, Francisco
Moroń, Tomasz
dc.contributor.author.none.fl_str_mv Giraldo-Guzmán, Jader
Contreras-Ortiz, Sonia H.
Kotas, Marian
Castells, Francisco
Moroń, Tomasz
dc.subject.keywords.spa.fl_str_mv Atrial Fibrillation;
Supraventricular Premature Beat;
Brain Ischemia
topic Atrial Fibrillation;
Supraventricular Premature Beat;
Brain Ischemia
LEMB
dc.subject.armarc.none.fl_str_mv LEMB
description Cardiovascular diseases are the main cause of death in the world, according to the World Health Organization. Among them, ischemic heart disease is at the top, followed by a stroke. Several studies have revealed that atrial fibrillation (AF), which is the most common cardiac arrhythmia, increases up to five fold the overall risk of stroke. As AF can be asymptomatic, approximately 20% of the AF cases remain undiagnosed. AF can be detected by analyzing electrocardiography records. Many studies have been conducted to develop automatic methods for AF detection. This paper reviews some of the most relevant methods, classified into three groups: analysis of heart rate variability, analysis of the atrial activity, and hybrid methods. Their benefits and limitations are analyzed and compared, and our beliefs about where AF automatic detection research could be addressed are presented to improve its effectiveness and performance. © 2021 by Begell House, Inc.
publishDate 2021
dc.date.issued.none.fl_str_mv 2021
dc.date.accessioned.none.fl_str_mv 2023-07-21T15:53:02Z
dc.date.available.none.fl_str_mv 2023-07-21T15:53:02Z
dc.date.submitted.none.fl_str_mv 2023
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dc.identifier.citation.spa.fl_str_mv Giraldo-Guzman, J., Contreras-Ortiz, S. H., Kotas, M., Castells, F., & Moron, T. (2021). Automated Atrial Fibrillation Detection by ECG Signal Processing: A Review. Critical Reviews™ in Biomedical Engineering, 49(3).
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/12297
dc.identifier.doi.none.fl_str_mv 10.1615/CritRevBiomedEng.2022041650
dc.identifier.instname.spa.fl_str_mv Universidad Tecnológica de Bolívar
dc.identifier.reponame.spa.fl_str_mv Repositorio Universidad Tecnológica de Bolívar
identifier_str_mv Giraldo-Guzman, J., Contreras-Ortiz, S. H., Kotas, M., Castells, F., & Moron, T. (2021). Automated Atrial Fibrillation Detection by ECG Signal Processing: A Review. Critical Reviews™ in Biomedical Engineering, 49(3).
10.1615/CritRevBiomedEng.2022041650
Universidad Tecnológica de Bolívar
Repositorio Universidad Tecnológica de Bolívar
url https://hdl.handle.net/20.500.12585/12297
dc.language.iso.spa.fl_str_mv eng
language eng
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dc.rights.cc.*.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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dc.format.extent.none.fl_str_mv 20 páginas
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dc.publisher.place.spa.fl_str_mv Cartagena de Indias
dc.source.spa.fl_str_mv Biomedical Engineering, 49(3)
institution Universidad Tecnológica de Bolívar
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spelling Giraldo-Guzmán, Jader3d51dd20-1ff3-4272-aac3-a64b2c5356adContreras-Ortiz, Sonia H.1d56d7f5-97c9-4429-b47d-48ebe97de2a8Kotas, Marian115f4d30-ba45-4bf6-bf66-152b622af835Castells, Francisco7fe49a07-6f9d-4462-adda-2fc09a85104aMoroń, Tomaszc19a62a6-ff70-425f-9d99-b7d695543d6a2023-07-21T15:53:02Z2023-07-21T15:53:02Z20212023Giraldo-Guzman, J., Contreras-Ortiz, S. H., Kotas, M., Castells, F., & Moron, T. (2021). Automated Atrial Fibrillation Detection by ECG Signal Processing: A Review. Critical Reviews™ in Biomedical Engineering, 49(3).https://hdl.handle.net/20.500.12585/1229710.1615/CritRevBiomedEng.2022041650Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarCardiovascular diseases are the main cause of death in the world, according to the World Health Organization. Among them, ischemic heart disease is at the top, followed by a stroke. Several studies have revealed that atrial fibrillation (AF), which is the most common cardiac arrhythmia, increases up to five fold the overall risk of stroke. As AF can be asymptomatic, approximately 20% of the AF cases remain undiagnosed. AF can be detected by analyzing electrocardiography records. Many studies have been conducted to develop automatic methods for AF detection. This paper reviews some of the most relevant methods, classified into three groups: analysis of heart rate variability, analysis of the atrial activity, and hybrid methods. Their benefits and limitations are analyzed and compared, and our beliefs about where AF automatic detection research could be addressed are presented to improve its effectiveness and performance. © 2021 by Begell House, Inc.20 páginasapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Biomedical Engineering, 49(3)Automated Atrial Fibrillation Detection by ECG Signal Processing: A Reviewinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_2df8fbb1Atrial Fibrillation;Supraventricular Premature Beat;Brain IschemiaLEMBCartagena de Indias(2006) Working together for health: The world health report 2006: Policy briefs. Cited 969 times. Geneva: World Health OrgGomez, LA. Las enfermedades cardiovasculares: Un problema de salud pública y un reto global (2011) Biomedica, 31 (4). Cited 5 times.Scott, L., Li, N., Dobrev, D. Role of inflammatory signaling in atrial fibrillation (2019) International Journal of Cardiology, 287, pp. 195-200. Cited 82 times. www.elsevier.com/locate/ijcard doi: 10.1016/j.ijcard.2018.10.020Wolf, P.A., Abbott, R.D., Kannel, W.B. Atrial fibrillation as an independent risk factor for stroke: The framingham study (1991) Stroke, 22 (8), pp. 983-988. Cited 5873 times. doi: 10.1161/01.STR.22.8.983(2017) Cardiovascular diseases. Cited 364 times. Geneva: World Health Org; From http://www.who.int/mediacentre/fact-sheets/fs317/en/Clua-Espuny, J.L., Lechuga-Duran, I., Bosch-Princep, R., Roso-Llorach, A., Panisello-Tafalla, A., Lucas-Noll, J., López-Pablo, C., (...), Gallofré López, M. Prevalence of undiagnosed atrial fibrillation and of that not being treated with anticoagulant drugs: The AFABE study (2013) Revista Espanola de Cardiologia, 66 (7), pp. 545-552. Cited 56 times. doi: 10.1016/j.recesp.2013.03.006Cervigón, R., Moreno, J., Castells, F. Entropy analysis of atrial activity morphology to study atrial fibrillation recurrences after ablation procedure (2015) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9043, pp. 146-154. Cited 5 times. https://www.springer.com/series/558 ISBN: 978-331916482-3 doi: 10.1007/978-3-319-16483-0_14Cervigon, R., Moreno, J., Millet, J., Castells, F. Multiscale principal component analysis to predict atrial fibrillation reversion to sinus rhythm (2016) Computing in Cardiology, 43, art. no. 7868780, pp. 465-468. Cited 2 times. http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000157 ISBN: 978-150900896-4Cervigon, R., Moreno, J., Millet, J., Castells, F. Singular Spectrum Analysis of Atrial Activations to Predict Atrial Fibrillation Recurrence after Ablation Procedure (2018) Computing in Cardiology, 2018-September, art. no. 8743856. http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000157 ISBN: 978-172810958-9 doi: 10.22489/CinC.2018.360Reiffel, J.A., Verma, A., Kowey, P.R., Halperin, J.L., Gersh, B.J., Wachter, R., Pouliot, E., (...), Ziegler, P.D. Incidence of previously undiagnosed atrial fibrillation using insertable cardiac monitors in a high-risk population: The REVEAL AF study (2017) JAMA Cardiology, 2 (10), pp. 1120-1127. Cited 171 times. https://jamanetwork.com/journals/jamacardiology/articlepdf/2650790/jamacardiology_reiffel_2017_oi_170047.pdf doi: 10.1001/jamacardio.2017.3180Cotter, P.E., Martin, M.P.J., Ring, L., Warburton, E.A., Belham, M., Pugh, P.J. 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