ECG-based heartbeat classification for arrhythmia detection : a survey.

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorLuz, Eduardo José da Silva-
Autor(es): dc.creatorSchwartz, William Robson-
Autor(es): dc.creatorCámara Chávez, Guillermo-
Autor(es): dc.creatorGomes, David Menotti-
Data de aceite: dc.date.accessioned2025-08-21T15:11:56Z-
Data de disponibilização: dc.date.available2025-08-21T15:11:56Z-
Data de envio: dc.date.issued2016-10-03-
Data de envio: dc.date.issued2016-10-03-
Data de envio: dc.date.issued2016-
Fonte completa do material: dc.identifierhttp://www.repositorio.ufop.br/handle/123456789/7011-
Fonte completa do material: dc.identifierhttps://doi.org/10.1016/j.cmpb.2015.12.008-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1005435-
Descrição: dc.descriptionAn electrocardiogram (ECG) measures the electric activity of the heart and has been widelyused for detecting heart diseases due to its simplicity and non-invasive nature. By analyzingthe electrical signal of each heartbeat, i.e., the combination of action impulse waveformsproduced by different specialized cardiac tissues found in the heart, it is possible to detectsome of its abnormalities. In the last decades, several works were developed to produceautomatic ECG-based heartbeat classification methods. In this work, we survey the currentstate-of-the-art methods of ECG-based automated abnormalities heartbeat classificationby presenting the ECG signal preprocessing, the heartbeat segmentation techniques, thefeature description methods and the learning algorithms used. In addition, we describesome of the databases used for evaluation of methods indicated by a well-known standarddeveloped by the Association for the Advancement of Medical Instrumentation (AAMI) anddescribed in ANSI/AAMI EC57:1998/(R)2008 (ANSI/AAMI, 2008). Finally, we discuss limitationsand drawbacks of the methods in the literature presenting concluding remarks and futurechallenges, and also we propose an evaluation process workflow to guide authors in futureworks.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Direitos: dc.rightsaberto-
Direitos: dc.rightsO periódico Computer Methods and Programs in Biomedicine concede permissão para depósito deste artigo no Repositório Institucional da UFOP. Número da licença: 3926560893208.-
Palavras-chave: dc.subjectECG-based signal processing-
Palavras-chave: dc.subjectHeartbeat classification-
Palavras-chave: dc.subjectPreprocessing-
Palavras-chave: dc.subjectHeartbeat segmentation-
Palavras-chave: dc.subjectFeature extraction-
Título: dc.titleECG-based heartbeat classification for arrhythmia detection : a survey.-
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