Weighted conditional random fields for supervised interpatient heartbeat classification

de Lannoy, Gaël;François, Damien;Delbeke, Jean;Verleysen, Michel
(2012) IEEE Transactions on Biomedical Engineering — Vol. 59, n° 1, p. 241-247 (2012)

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Abstract
This paper proposes a method for the automatic classification of heartbeats in an ECG signal. Since this task has specific characteristics such as time dependences between observations and a strong class unbalance, a specific classifier is proposed and evaluated on real ECG signals from the MIT arrhythmia database. This classifier is a weighted variant of the conditional random fields classifier. Experiments show that the proposed method outperforms previously reported heartbeat classification methods, especially for the pathological heartbeats.
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de Lannoy, G., François, D., Delbeke, J., & Verleysen, M. (2012). Weighted conditional random fields for supervised interpatient heartbeat classification. IEEE Transactions on Biomedical Engineering, 59(1), 241-247. https://doi.org/10.1109/TBME.2011.2171037 (Original work published 2012)