Title: Descendant adaptive filter to remove different noises from ECG signals

Authors: Mangesh Ramaji Kose; Mitul Kumar Ahirwal; Rekh Ram Janghel

Addresses: Department of Computer Applications, National Institute of Technology, Raipur – 492010, India ' Department of Computer Applications, National Institute of Technology, Raipur – 492010, India ' Department of Information Technology, National Institute of Technology, Raipur – 492010, India

Abstract: Electrocardiogram (ECG) signals are electrical signals generated corresponding to activity of heart. ECG signals are recorded and analysed to monitor heart condition. In initial raw form, ECG signals are contaminated with different types of noises. These noises may be electrode motion artefact noise, baseline wander noise and muscle noise also known as electromyogram (EMG) noise etc. In this paper, a descendent structure consists of adaptive filters is used to eliminate the three different types of noises (i.e., motion artefact noise, baseline wander noise and muscle noise). The two different adaptive filtering algorithms have been implemented; least mean square (LMS) and recursive least square (RLS) algorithm. The performance of these filters are compared on the basis of different fidelity parameters such as mean square error (MSE), normalised root mean squared error (NRMSE), signal-to-noise ratio (SNR), percentage root mean squared difference (PRD), and maximum error (ME) has been observed.

Keywords: adaptive filters; electrocardiogram; ECG; artefacts; least mean square; LMS; recursive least square; RLS; SMA.

DOI: 10.1504/IJBET.2020.10029989

International Journal of Biomedical Engineering and Technology, 2020 Vol.33 No.3, pp.258 - 273

Received: 06 Jul 2017
Accepted: 11 Oct 2017

Published online: 15 Jun 2020 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article