Inter-patient ECG heartbeat classification with temporal VCG optimized by PSO.
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFOP |
Texto Completo: | http://www.repositorio.ufop.br/handle/123456789/9392 https://doi.org/10.1038/s41598-017-09837-3 |
Resumo: | Classifying arrhythmias can be a tough task for a human being and automating this task is highly desirable. Nevertheless fully automatic arrhythmia classification through Electrocardiogram (ECG) signals is a challenging task when the inter-patient paradigm is considered. For the inter-patient paradigm, classifiers are evaluated on signals of unknown subjects, resembling the real world scenario. In this work, we explore a novel ECG representation based on vectorcardiogram (VCG), called temporal vectorcardiogram (TVCG), along with a complex network for feature extraction. We also fine-tune the SVM classifier and perform feature selection with a particle swarm optimization (PSO) algorithm. Results for the inter-patient paradigm show that the proposed method achieves the results comparable to state-of-the-art in MIT-BIH database (53% of Positive predictive (+P) for the Supraventricular ectopic beat (S) class and 87.3% of Sensitivity (Se) for the Ventricular ectopic beat (V) class) that TVCG is a richer representation of the heartbeat and that it could be useful for problems involving the cardiac signal and pattern recognition. |
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Garcia, GabrielMoreira, Gladston Juliano PratesGomes, David MenottiLuz, Eduardo José da Silva2018-01-30T13:44:34Z2018-01-30T13:44:34Z2017GARCIA, G. et al. Inter-patient ECG heartbeat classification with temporal VCG optimized by PSO. Scientific Reports, v. 7, p. 1-11, 2017. Disponível em: <https://www.nature.com/articles/s41598-017-09837-3>. Acesso em: 16 jan. 2018.2045-2322http://www.repositorio.ufop.br/handle/123456789/9392https://doi.org/10.1038/s41598-017-09837-3Classifying arrhythmias can be a tough task for a human being and automating this task is highly desirable. Nevertheless fully automatic arrhythmia classification through Electrocardiogram (ECG) signals is a challenging task when the inter-patient paradigm is considered. For the inter-patient paradigm, classifiers are evaluated on signals of unknown subjects, resembling the real world scenario. In this work, we explore a novel ECG representation based on vectorcardiogram (VCG), called temporal vectorcardiogram (TVCG), along with a complex network for feature extraction. We also fine-tune the SVM classifier and perform feature selection with a particle swarm optimization (PSO) algorithm. Results for the inter-patient paradigm show that the proposed method achieves the results comparable to state-of-the-art in MIT-BIH database (53% of Positive predictive (+P) for the Supraventricular ectopic beat (S) class and 87.3% of Sensitivity (Se) for the Ventricular ectopic beat (V) class) that TVCG is a richer representation of the heartbeat and that it could be useful for problems involving the cardiac signal and pattern recognition.Os trabalhos publicados no periódico Scientific Reports estão sob Licença Creative Commons que permite copiar, distribuir e transmitir o trabalho desde que sejam citados o autor e o licenciante. Fonte: Sherpa/Romeo <http://www.sherpa.ac.uk/romeo/search.php?issn=2045-2322>. Acesso em: 27 fev. 2020.info:eu-repo/semantics/openAccessInter-patient ECG heartbeat classification with temporal VCG optimized by PSO.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleengreponame:Repositório Institucional da UFOPinstname:Universidade Federal de Ouro Preto (UFOP)instacron:UFOPLICENSElicense.txtlicense.txttext/plain; charset=utf-8924http://www.repositorio.ufop.br/bitstream/123456789/9392/2/license.txt62604f8d955274beb56c80ce1ee5dcaeMD52ORIGINALARTIGO_InterPatientECG.pdfARTIGO_InterPatientECG.pdfapplication/pdf2093289http://www.repositorio.ufop.br/bitstream/123456789/9392/1/ARTIGO_InterPatientECG.pdf39604474a8cc05ecbab104e2996bada6MD51123456789/93922020-02-27 08:43:57.866oai:localhost: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ório InstitucionalPUBhttp://www.repositorio.ufop.br/oai/requestrepositorio@ufop.edu.bropendoar:32332020-02-27T13:43:57Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)false |
dc.title.pt_BR.fl_str_mv |
Inter-patient ECG heartbeat classification with temporal VCG optimized by PSO. |
title |
Inter-patient ECG heartbeat classification with temporal VCG optimized by PSO. |
spellingShingle |
Inter-patient ECG heartbeat classification with temporal VCG optimized by PSO. Garcia, Gabriel |
title_short |
Inter-patient ECG heartbeat classification with temporal VCG optimized by PSO. |
title_full |
Inter-patient ECG heartbeat classification with temporal VCG optimized by PSO. |
title_fullStr |
Inter-patient ECG heartbeat classification with temporal VCG optimized by PSO. |
title_full_unstemmed |
Inter-patient ECG heartbeat classification with temporal VCG optimized by PSO. |
title_sort |
Inter-patient ECG heartbeat classification with temporal VCG optimized by PSO. |
author |
Garcia, Gabriel |
author_facet |
Garcia, Gabriel Moreira, Gladston Juliano Prates Gomes, David Menotti Luz, Eduardo José da Silva |
author_role |
author |
author2 |
Moreira, Gladston Juliano Prates Gomes, David Menotti Luz, Eduardo José da Silva |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Garcia, Gabriel Moreira, Gladston Juliano Prates Gomes, David Menotti Luz, Eduardo José da Silva |
description |
Classifying arrhythmias can be a tough task for a human being and automating this task is highly desirable. Nevertheless fully automatic arrhythmia classification through Electrocardiogram (ECG) signals is a challenging task when the inter-patient paradigm is considered. For the inter-patient paradigm, classifiers are evaluated on signals of unknown subjects, resembling the real world scenario. In this work, we explore a novel ECG representation based on vectorcardiogram (VCG), called temporal vectorcardiogram (TVCG), along with a complex network for feature extraction. We also fine-tune the SVM classifier and perform feature selection with a particle swarm optimization (PSO) algorithm. Results for the inter-patient paradigm show that the proposed method achieves the results comparable to state-of-the-art in MIT-BIH database (53% of Positive predictive (+P) for the Supraventricular ectopic beat (S) class and 87.3% of Sensitivity (Se) for the Ventricular ectopic beat (V) class) that TVCG is a richer representation of the heartbeat and that it could be useful for problems involving the cardiac signal and pattern recognition. |
publishDate |
2017 |
dc.date.issued.fl_str_mv |
2017 |
dc.date.accessioned.fl_str_mv |
2018-01-30T13:44:34Z |
dc.date.available.fl_str_mv |
2018-01-30T13:44:34Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
GARCIA, G. et al. Inter-patient ECG heartbeat classification with temporal VCG optimized by PSO. Scientific Reports, v. 7, p. 1-11, 2017. Disponível em: <https://www.nature.com/articles/s41598-017-09837-3>. Acesso em: 16 jan. 2018. |
dc.identifier.uri.fl_str_mv |
http://www.repositorio.ufop.br/handle/123456789/9392 |
dc.identifier.issn.none.fl_str_mv |
2045-2322 |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1038/s41598-017-09837-3 |
identifier_str_mv |
GARCIA, G. et al. Inter-patient ECG heartbeat classification with temporal VCG optimized by PSO. Scientific Reports, v. 7, p. 1-11, 2017. Disponível em: <https://www.nature.com/articles/s41598-017-09837-3>. Acesso em: 16 jan. 2018. 2045-2322 |
url |
http://www.repositorio.ufop.br/handle/123456789/9392 https://doi.org/10.1038/s41598-017-09837-3 |
dc.language.iso.fl_str_mv |
eng |
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eng |
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openAccess |
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