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Identification of Cardiac Arrhythmia with respect to ECG Signal by Neural Networks and Genetic Programming

Nalla.Srinivas, A.Vinay Babu, M.D.Rajak, Syed Musthak Ahmed

In this paper analysis of „Electrocardiogram (ECG) PQRSTU-waveforms and prediction of particular decease infection or state of a patient is done using Genetic Algorithm and Artificial Neural Network (ANN), precise Electrocardiogram (ECG) classification to diagnose patientâ�?�?s condition is essential. For classification of such difficult-to-diagnose-signals, i.e. ECG signal, classification is performed using various pulses, like v1, v2, v3, v4, v5, v6 etc corresponding hidden layer in ANN i.e., P-Wave, PR-Interval, QRS-Interval, ST-Interval, T-Wave etc analysis of each Input pulse used to train the neural network. Output of the neural network gives weight factors of each signal to create a data set. Corresponding output-datasets indicates related disease and predict the causes. And results are analyzed by Genetic Algorithm.