Recognition of ecg arrhythmias using back propagation Neural network

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Pooja Kalra
Ankita Mittal, Saurabh Mittal


In this paper, the back propagation neural network method used for Electrocardiogram (ECG) Arrhythmia recognition. Different types
of ECG patterns were chosen from the real database to be recognized, including normal sinus rhythm, premature ventricular contraction, atrial
premature beat and left bundle branch block beat. ECG wave and different interval features were performed as the characteristic representation
of the original ECG signals to be fed into the neural network models. Back propagation neural networks will be separately trained and tested for
ECG Arrhythmias recognition. The objective is to find different arrhythmias of different patients by analyzing the different ECGS with their
parameters using back propagation network.[1,2] In this paper we are using MATLAB for implementation of training and testing of neural



Keywords: Neural Networks, BPN, ECG, Recognition


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