ECG signal denoising by using least-mean-square and normalised-least-mean-square algorithm based adaptive filter

Abstract

Electrocardiogram (ECG) is a method of measuring the electrical activities of heart. Every portion of ECG is very essential for the diagnosis of different cardiac problems. But the amplitude and duration of ECG signal is usually corrupted by different noises. In this paper we have done a broader study for denoising every types of noise involved with real ECG signal. Two adaptive filters, such as, least-mean-square (LMS) and normalized-least-mean-square (NLMS) are applied to remove the noises. For better clarification simulation results are compared in terms of different performance parameters such as, power spectral density (PSD), spectrogram, frequency spectrum and convergence. SNR, %PRD and MSE performance parameter are also estimated. Signal Processing Toolbox built in MATLAB ^® is used for simulation, and, the simulation result clarifies that adaptive NLMS filter is an excellent method for denoising the ECG signal.