SUPERVISED CLASSIFICATION OF ECG USING NEURAL NETWORKS

Abstract

In this study, two kinds of neural networks are employed to develop a supervised ECG beat classifier. In order to improve the performance of the MLP classifier for application to ECG signal, the performance is compared to an LVQ neural network classifier. The two classifiers are tested with selected ECG time series and experimental results show that the MLP classifier offers a great potential in the supervised classification of ECG beats.