ECG Signal Denoising by Using Least-Mean-Square Based Adaptive Filter

Abstract

Electrocardiogram (ECG) is a method of measuringthe electrical activities of heart. Every portion of ECG is veryessential for the diagnosis of different cardiac problems. But theamplitude and duration of ECG signal is usually corrupted bydifferent noises. In this paper we have done a broader study fordenoising every types of noise involved with real ECG signal.Two adaptive filters, such as, least-mean-square (LMS) andnormalized-least- mean-square (NLMS) are applied to remove thenoises. For better clarification simulation results are compared interms of different performance parameters such as, powerspectral density (PSD), spectrogram, frequency spectrum andconvergence. SNR, %PRD and MSE perfor- mance parameter arealso estimated. Signal Processing Toolbox built in MATLAB® isused for simulation, and, the simulation result clarifies thatadaptive NLMS filter is an excellent method for denoising theECG signal.