Noise Removal of ECG Signal Using Recursive LeastSquare Algorithms

Noise Removal of ECG Signal Using Recursive LeastSquare Algorithms

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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). S...

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Bibliographic Details
Main Author: Noor K. Muhsin
Format: Article
Language:English
Published: Al-Khwarizmi College of Engineering – University of Baghdad 2011-01-01
Series:Al-Khawarizmi Engineering Journal
Subjects:
Adaptive filters
RLS algorithms
noise
ECG signals
signal processing.
Online Access:http://www.iasj.net/iasj?func=fulltext&aId=2222
Description
Summary: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.
ISSN:1818-1171

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