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...

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Detalhes bibliográficos
Autores: Giraldo-Guzmán, Jader, Contreras-Ortiz, Sonia H., Kotas, Marian, Castells, Francisco, Moroń, Tomasz
Formato: artículo
Estado:Versión borrador
Fecha de publicación:2021
País:Colombia
Recursos:Universidad Tecnológica de Bolívar
Repositorio:Repositorio Institucional UTB
Idioma:inglés
OAI Identifier:oai:repositorio.utb.edu.co:20.500.12585/12297
Acesso em linha:https://hdl.handle.net/20.500.12585/12297
Access Level:acceso abierto
Palavra-chave:Atrial Fibrillation;
Supraventricular Premature Beat;
Brain Ischemia
LEMB
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spelling Automated Atrial Fibrillation Detection by ECG Signal Processing: A ReviewGiraldo-Guzmán, JaderContreras-Ortiz, Sonia H.Kotas, MarianCastells, FranciscoMoroń, TomaszAtrial Fibrillation;Supraventricular Premature Beat;Brain IschemiaLEMBCardiovascular 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.Cartagena de Indias2023-07-21T15:53:02Z2023-07-21T15:53:02Z20212023info:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_650120 páginasapplication/pdfapplication/pdfGiraldo-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 BolívarBiomedical Engineering, 49(3)reponame:Repositorio Institucional UTBinstname:Universidad Tecnológica de Bolívarinstacron:Universidad Tecnológica de Bolívarenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacional2023-07-22T05:17:58Z
dc.title.none.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
Giraldo-Guzmán, Jader
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.none.fl_str_mv Giraldo-Guzmán, Jader
Contreras-Ortiz, Sonia H.
Kotas, Marian
Castells, Francisco
Moroń, Tomasz
author Giraldo-Guzmán, Jader
author_facet Giraldo-Guzmán, Jader
Contreras-Ortiz, Sonia H.
Kotas, Marian
Castells, Francisco
Moroń, Tomasz
author_role author
author2 Contreras-Ortiz, Sonia H.
Kotas, Marian
Castells, Francisco
Moroń, Tomasz
author2_role author
author
author
author
dc.subject.none.fl_str_mv Atrial Fibrillation;
Supraventricular Premature Beat;
Brain Ischemia
LEMB
topic Atrial Fibrillation;
Supraventricular Premature Beat;
Brain Ischemia
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.none.fl_str_mv 2021
2023-07-21T15:53:02Z
2023-07-21T15:53:02Z
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/draft
http://purl.org/coar/resource_type/c_6501
format article
status_str draft
dc.identifier.none.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).
https://hdl.handle.net/20.500.12585/12297
10.1615/CritRevBiomedEng.2022041650
Universidad Tecnológica de Bolívar
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.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 20 páginas
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Cartagena de Indias
publisher.none.fl_str_mv Cartagena de Indias
dc.source.none.fl_str_mv Biomedical Engineering, 49(3)
reponame:Repositorio Institucional UTB
instname:Universidad Tecnológica de Bolívar
instacron:Universidad Tecnológica de Bolívar
instname_str Universidad Tecnológica de Bolívar
instacron_str Universidad Tecnológica de Bolívar
institution Universidad Tecnológica de Bolívar
reponame_str Repositorio Institucional UTB
collection Repositorio Institucional UTB
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score 15,812429

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