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Title: Evaluating a hierarchical approach for heartbeat classification from ECG.
Authors: Luz, Eduardo José da Silva
Merschmann, Luiz Henrique de Campos
Menotti, David
Moreira, Gladston Juliano Prates
Keywords: Biomedical engineering
ECG analysis
Hierarchical classification
Issue Date: 2018
Citation: LUZ, E. J. da s. et al. Evaluating a hierarchical approach for heartbeat classification from ECG. International Journal of Bioinformatics Research and Applications, v. 13, p. 146, 2017. Disponível em: <>. Acesso em: 16 jun. 2018.
Abstract: Several types of arrhythmias that can be rare and harmless, but may result in serious cardiac issues, and several ECG analysis methods have been proposed in the literature to automatically classify the various classes of arrhythmias. Following the Association for the Advancement of Medical Instrumentation (AAMI) standard, 15 classes of heartbeats can be hierarchically grouped into five superclasses. In this work, we propose to employ the hierarchical classification paradigm to five ECG analysis methods in the literature, and compare their performance with flat classification paradigm. In our experiments, we use the MIT-BIH Arrhythmia Database and analyse the use of the hierarchical classification following AAMI standard and a well-known and established evaluation protocol using five superclasses. The experimental results showed that the hierarchical classification provided the highest gross accuracy for most of the methods used in this work and provided an improvement in classification performance of N and SVEB superclasses.
ISSN: 17445493
Appears in Collections:DECOM - Artigos publicados em periódicos

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