Evaluating a hierarchical approach for heartbeat classification from ECG.
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Date
2018
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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.
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Keywords
Biomedical engineering, ECG analysis, Arrhythmias, Hierarchical classification
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: <https://www.inderscienceonline.com/doi/pdf/10.1504/IJBRA.2017.083148>. Acesso em: 16 jun. 2018.