JDP_V2_N4_RP2 Application of Polynomial Approximation Techniques for Smoothing ECG Signals Ashish Rohila V.K. Giri Journal on Digital Signal Processing 2322–0368 2 4 8 13 ECG, PRD, PSD, Polynomial Filter, Smoothing, Curve Fitting Technique Electrocardiogram (ECG) is the recording of the electrical activities of the heart. ECG signals are recorded on the body surface with the help of surface electrodes. While recording, different artifacts get introduced in the signal like; electrode contact noise, motion artifacts, base line drift, base line wander, electrosurgical noise, and power line interferences. Some kind of signal processing is required to get meaningful information from ECG. Now a days digital signal processing is preferred over analog signal processing. Various digital signal processing techniques have been developed over a period of last four decades for removing noise from ECG signal. The curve fitting is a simple and widely used technique for smoothing ECG signal (removing high frequency noise). In this paper we have presented a comparison study of various smoothing filters to filter high frequency noise. To compare performance of various smoothing filters Power Spectral Density (PSD), Average Power and Percent Root mean square Difference (PRD) have been calculated. October - December 2014 Copyright © 2014 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=3142