CLASSIFICATION OF HEART RATE USING BACK PROPAGATION NEURAL NETWORKS

Abstract

A condition of abnormal electrical activity in the heart which is a threat to humans is shown by this electrocardiogram. It is a representative signal containing information about the condition of the heart. The of the P-QRS-T wave shape and size and their time intervals between its various peaks these are all contain useful information about the nature of disease affecting the heart. This paper presents a technique to examine electrocardiogram (ECG) signal, take out the features for the heart beats classification. Collect data from MIT-BIH database. The heart rate is used as the base signal from which certain parameters are extracted and presented to the BPN for classification.