Neural Network based indicative ECG classification

The Electrocardiogram (ECG) is undoubtedly the most used biological signal in the clinical world and it is a means for detection of several cardiac abnormalities. Pattern recognition, diagnostic classification of ECGs constitutes an interesting application of Artificial Neural Networks (ANNs). This paper illustrates the ability of a feed-forward back propagation using Neural Network for classify unknown ECG waveforms keen on one of the 4 discrete class. Out of the 4 classes, 3 of them correspond to abnormal ECG signals and 1 represents the healthy group. In addition, the Neural Network model developed has the option to categorize unknown ECG input signals as unclassified, since it represents an unknown pathology. Preliminary results are obtained using data from 4 different Physiobank ECG database.