Application of Polynomial Approximation Techniques for Smoothing ECG Signals

Ashish Rohila*, V. K. Giri**
* M.Tech Student, Department of Electrical Engineering, MMM University of Technology, Gorakhpur, UP, India.
** Professor and Head, Department of Electrical Engineering, MMM University of Technology, Gorakhpur, UP, India.
Periodicity:October - December'2014


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.


ECG, PRD, PSD, Polynomial Filter, Smoothing, Curve Fitting Technique

How to Cite this Article?

Rohila,A., and Giri.V.K. (2014). Application Of Polynomial Approximation Techniques For Smoothing ECG Signals. i-manager’s Journal on Digital Signal Processing, 2(4), 8-13.


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