European Journal of Scientific Research ISSN 1450-216X Vol.66 No.3 (2011), pp. 441-448 © EuroJournals Publishing, Inc. 2011 http://www.europeanjournalofscientificresearch.com Arrhythmia Detection through ECG Feature Extraction using Wavelet Analysis V. Vijaya Assoc. Professor, Vaagdevi College of Engineering, Warangal E-mail: vsrtej@yahooo.co.in Tel: 9849997298 K. Kishan Rao Director, Vaagdevi College of Engineering, Warangal E-mail: kishanrao6@gmail.com Tel: 9440775866 V. Rama Asst.Professor, NIT, Warangal E-mail: vr.nitw@gmail.com Tel: 9440762744 Abstract Cardiac Arrhythmia is the most common causes of death .These abnormalities of heart may cause sudden cardiac arrest or cause damage to heart. Electrocardiogram (ECG) feature extraction system has developed and evaluated based on the multi-resolution wavelet transform. ECG Feature Extraction plays a significant role in diagnosing most of the cardiac diseases. One cardiac cycle in an ECG signal consists of the P-QRS-T waves. This feature extraction scheme determines the amplitudes and intervals in the ECG signal for subsequent analysis. The amplitudes and intervals of P-QRS-T segment determine the functioning of heart. The ECG signal was de-noised by removing the corresponding wavelet coefficients at higher scales. Then, QRS complexes are detected and each complex is used to locate the peaks of the individual waves, R-R intervals which are present in one cardiac cycle and evaluated the algorithm on MIT-BIH Database, the manually annotated database, for validation purposes. Keywords: Artifacts, CardiacArrhythmia, Electrocardiogram (ECG), Discrete Wavelet transform (DWT), Wavelet Decomposition, His bundle, atria, Atrioventricular (AV) node. 1. Introduction ECG interpretation is one of the most important upcoming areas and widely used clinical tool. Cardiac Arrhythmias are the most common causes of death, it is an abnormal rate of muscle contractions in the heart. These abnormalities of heart may cause sudden cardiac arrest or cause damage to heart. The primary aim of this paper is QRS detection of Electrocardiogram waveforms and abnormalities and hence facilitating early detection of cardiac problems.