Genetic Algorithm based Feature Extraction for ECG Signal Classification using Neural Network
- R. Sathya
- K. Akilandeswari
ECG Signal, Preprocessing, Fitness evaluation, Roulette Wheel selection.
Cardiac Arrhythmia is a key problem faced by many people regardless of age and gender. P wave, QRS complex and T wave forms a complete cardiac cycle. Absence or abnormal appearance of any waves lead to cardiac arrhythmia. If these abnormalities are diagnosed at the earliest stage, appropriate treatment can be provided to the patients. In our research work, classification technique in data mining is used for classifying normal and abnormal patients. Pan Tompkin algorithm is used for de-noising of Electrocardiogram (ECG) signals and to obtain QRS on filtered signal. Genetic algorithm and Neural network classifier are used to achieve high accuracy in classification of signals.
R. Sathya, K. Akilandeswari. "Genetic Algorithm based Feature Extraction for ECG Signal Classification using Neural Network".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.3, Issue 2, pp.1426-1430, URL :https://rjwave.org/ijedr/papers/IJEDR1502232.pdf
Volume 3 Issue 2
Pages. 1426-1430
