A Neural Network Approach for ECG Classification

Abstract

Abstract- bioelectrical signal, which records the heart’s electrical activity versus time, is an electrocardiogram (ECG). It is an important diagnostic tool for assessing heart functions. The interpretation of ECG signal is an application of pattern recognition. signal pre-processing, QRS detection, feature extraction and neural network for signal classification are those techniques which used in this pattern recognition comprise. There are Different ECG feature inputs were used in the experiments to compare and find a desirable features input for ECG classification. Among different structures, it was found that a three layer network structure with 25 inputs, 5 neurons in the output layer and 5 neurons in its hidden layers possessed the best performance with highest recognition rate of 91.8 % for five cardiac conditions. Keyword-- ECG, QRS, Neural Network I