Rede Bayesiana com Limiar de Decisão para Classificação de Batimentos Cardíacos (Bayesian Network with Decision Threshold for Heart Beat Classification)

Lorena Sophia Campos Oliveira (, Rodrigo Varejão Andreão (, Mário Sarcinelli Filho (

1Universidade Federal dos Vales do Jequitinhonha e Mucuri
2Instituto Federal de Educação, Ciência e Tecnologia do Espírito Santo
3Universidade Federal do Espírito Santo

This paper appears in: Revista IEEE América Latina

Publication Date: March 2016
Volume: 14,   Issue: 3 
ISSN: 1548-0992

This work proposes a Dynamic Bayesian Network approach (BN) to support medical decision making in the problem of beat classification in electrocardiograms. The BN takes the uncertainty into consideration when making a decision every time new evidence is available. Moreover, the certainty related to the beat classification can be controlled through a threshold adjusted by the specialist. The performance of the BN based classifier is assessed through the MIT-BIH database, considering two beat classes: Premature Ventricular Beat (PVC class) and Other (gathering all other beat classes). The BN with probability threshold of 0.75 achieved scores of Sensitivity and Positive Predictive of 99% for the PVC beats. The results show that the BN framework is a promising tool for classifying cardiac arrhythmias.

Index Terms:
Bayesian Network, Electrocardiogram, Beat classification, PVC detection   

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