Classification and Morphological Extraction of ECG Parameters

Abstract: Electrocardiogram (ECG) analysis is used to control and detect cardiac disorders. The amplitude and intervals of ECG control theproper functioning of heart. There is dissimilarity in the extracted features which belong to a normal ECG and irregular ECG hence these extracted features are valuable in ECG arrhythmia detection.Cardiac arrhythmia is a set of conditions in which the heartbeat is irregular, too slow, or too fast.This paper proposes ECG signal classification using anArtificial Neural Network classifier, based on feature extraction of the ECG signal with the help of signal processing algorithms. The management of cardiac disorders is doneby detecting and classifying the different ECG signals with the help of Artificial Neural Network. Keywords: Feature Extraction, Artificial Neural Network, ECG analysis, ECG Morphology, Noise Removal, Arrhythmia.