Abstrait

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 patientâÂ?Â?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.