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Paper Details
Paper Title
Genetic Algorithm based Feature Extraction for ECG Signal Classification using Neural Network
Authors
  R. Sathya,  K. Akilandeswari
Abstract
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.
Keywords- ECG Signal, Preprocessing, Fitness evaluation, Roulette Wheel selection.
Publication Details
Unique Identification Number - IJEDR1502232Page Number(s) - 1426-1430Pubished in - Volume 3 | Issue 2 | May 2015DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  R. Sathya,  K. Akilandeswari,   "Genetic Algorithm based Feature Extraction for ECG Signal Classification using Neural Network", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.3, Issue 2, pp.1426-1430, May 2015, Available at :http://www.ijedr.org/papers/IJEDR1502232.pdf
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