Recognition of Heartbeats Using Support Vector Machine Networks - A Comparative Study

The paper presents the comparison of performance of the individual and ensemble of SVM classifiers for the recognition of abnormal heartbeats on the basis of the registered ECG waveforms. The recognition system applies two different Support Vector Machine based classifiers and the ensemble systems composed of the individual classifiers combined together in different way to obtain the best possible performance on the ECG data. The results of numerical experiments using the data of MIT BIH Arrhythmia Database have confirmed the superior performance of the proposed solution.

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