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

dc.contributor.authorLuz, Eduardo José da Silva
dc.contributor.authorSchwartz, William Robson
dc.contributor.authorCámara Chávez, Guillermo
dc.contributor.authorGomes, David Menotti
dc.date.accessioned2016-10-03T17:59:49Z
dc.date.available2016-10-03T17:59:49Z
dc.date.issued2016
dc.description.abstractAn 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.pt_BR
dc.identifier.citationLUZ, E. J. da S. et al. ECG-based heartbeat classification for arrhythmia detection: a survey. Computer Methods and Programs in Biomedicine, v. 127, p. 144-164, 2016. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0169260715003314>. Acesso em: 07 ago. 2016.pt_BR
dc.identifier.doihttps://doi.org/10.1016/j.cmpb.2015.12.008
dc.identifier.issn0169-2607
dc.identifier.urihttp://www.repositorio.ufop.br/handle/123456789/7011
dc.language.isoen_USpt_BR
dc.rightsabertopt_BR
dc.rights.licenseO periódico Computer Methods and Programs in Biomedicine concede permissão para depósito deste artigo no Repositório Institucional da UFOP. Número da licença: 3926560893208.pt_BR
dc.subjectECG-based signal processingpt_BR
dc.subjectHeartbeat classificationpt_BR
dc.subjectPreprocessingpt_BR
dc.subjectHeartbeat segmentationpt_BR
dc.subjectFeature extractionpt_BR
dc.titleECG-based heartbeat classification for arrhythmia detection : a survey.pt_BR
dc.typeArtigo publicado em periodicopt_BR
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