Noise Removal of ECG Signal Using Recursive Least Square Algorithms

  • Noor K. Muhsin Department of Biomedical Engineering/ Al-Khwarizmi College of Engineering/ University of Baghdad

Abstract

This paper shows an approach for Electromyography (ECG) signal processing based on linear and nonlinear adaptive filtering using Recursive Least Square (RLS) algorithm to remove two kinds of noise that affected the ECG signal. These are the High Frequency Noise (HFN) and Low Frequency Noise (LFN). Simulation is performed in Matlab. The ECG, HFN and LFN signals used in this study were downloaded from ftp://ftp.ieee.org/uploads/press/rangayyan/, and then the filtering process was obtained by using adaptive finite impulse response (FIR) that illustrated better results than infinite impulse response (IIR) filters did.

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References

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Published
2011-03-01
How to Cite
Muhsin, N. (2011). Noise Removal of ECG Signal Using Recursive Least Square Algorithms. Al-Khwarizmi Engineering Journal, 7(1), 13-21. Retrieved from https://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/464