Heart disease detection using ECG lead I and multiple pattern recognition classifiers

Detalhes bibliográficos
Autor(a) principal: Pereira, Renato
Data de Publicação: 2020
Outros Autores: Bispo, Bruno, Rodrigues, Pedro Miguel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.14/32993
Resumo: ECG is an important tool to assist in heart diseases diagnosis. The works found in the literature have the common goal of discriminating between binary study groups, one pathological and one control, even when ECG records from patients diagnosed with several pathologies are available in the databases. This work proposes a method to detect ECG morphological features and to analyze the capacity of this ECG features to discriminate 28 pairs of study groups, combining 7 pathological groups and 1 control group, presented in the PTB Diagnostic ECG Database. For each pair, it was achieved an accuracy between 77.4% and 100%, with an average of 94%, using several pattern recognition classifiers.
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spelling Heart disease detection using ECG lead I and multiple pattern recognition classifiersHeart diseasesECG featuresPattern recognitionPTB Diagnostic ECG databasesClassifiersECG is an important tool to assist in heart diseases diagnosis. The works found in the literature have the common goal of discriminating between binary study groups, one pathological and one control, even when ECG records from patients diagnosed with several pathologies are available in the databases. This work proposes a method to detect ECG morphological features and to analyze the capacity of this ECG features to discriminate 28 pairs of study groups, combining 7 pathological groups and 1 control group, presented in the PTB Diagnostic ECG Database. For each pair, it was achieved an accuracy between 77.4% and 100%, with an average of 94%, using several pattern recognition classifiers.Veritati - Repositório Institucional da Universidade Católica PortuguesaPereira, RenatoBispo, BrunoRodrigues, Pedro Miguel2021-05-11T10:28:23Z2020-04-042020-04-04T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.14/32993eng2278-87192250-3021info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-12T17:38:30Zoai:repositorio.ucp.pt:10400.14/32993Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:26:38.836604Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Heart disease detection using ECG lead I and multiple pattern recognition classifiers
title Heart disease detection using ECG lead I and multiple pattern recognition classifiers
spellingShingle Heart disease detection using ECG lead I and multiple pattern recognition classifiers
Pereira, Renato
Heart diseases
ECG features
Pattern recognition
PTB Diagnostic ECG databases
Classifiers
title_short Heart disease detection using ECG lead I and multiple pattern recognition classifiers
title_full Heart disease detection using ECG lead I and multiple pattern recognition classifiers
title_fullStr Heart disease detection using ECG lead I and multiple pattern recognition classifiers
title_full_unstemmed Heart disease detection using ECG lead I and multiple pattern recognition classifiers
title_sort Heart disease detection using ECG lead I and multiple pattern recognition classifiers
author Pereira, Renato
author_facet Pereira, Renato
Bispo, Bruno
Rodrigues, Pedro Miguel
author_role author
author2 Bispo, Bruno
Rodrigues, Pedro Miguel
author2_role author
author
dc.contributor.none.fl_str_mv Veritati - Repositório Institucional da Universidade Católica Portuguesa
dc.contributor.author.fl_str_mv Pereira, Renato
Bispo, Bruno
Rodrigues, Pedro Miguel
dc.subject.por.fl_str_mv Heart diseases
ECG features
Pattern recognition
PTB Diagnostic ECG databases
Classifiers
topic Heart diseases
ECG features
Pattern recognition
PTB Diagnostic ECG databases
Classifiers
description ECG is an important tool to assist in heart diseases diagnosis. The works found in the literature have the common goal of discriminating between binary study groups, one pathological and one control, even when ECG records from patients diagnosed with several pathologies are available in the databases. This work proposes a method to detect ECG morphological features and to analyze the capacity of this ECG features to discriminate 28 pairs of study groups, combining 7 pathological groups and 1 control group, presented in the PTB Diagnostic ECG Database. For each pair, it was achieved an accuracy between 77.4% and 100%, with an average of 94%, using several pattern recognition classifiers.
publishDate 2020
dc.date.none.fl_str_mv 2020-04-04
2020-04-04T00:00:00Z
2021-05-11T10:28:23Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.14/32993
url http://hdl.handle.net/10400.14/32993
dc.language.iso.fl_str_mv eng
language eng
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2250-3021
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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