Please use this identifier to cite or link to this item:
https://dspace.iiti.ac.in/handle/123456789/5827
Title: | Baseline wander and power line interference removal from ECG signals using eigenvalue decomposition |
Authors: | Pachori, Ram Bilas |
Keywords: | Eigenvalues and eigenfunctions;Electrocardiography;Matrix algebra;Signal interference;Signal to noise ratio;Baseline wander;ECG Denoising;Eigenvalue decomposition;Hankel matrix;Powerline interference;Biomedical signal processing;acoustic stress;algorithm;amplitude modulation;Article;baseline wander noise;cardiovascular parameters;comparative study;data base;decomposition;eigenvalue decomposition of Hankel matrix;electrocardiogram;empirical mode decomposition;extended kalman filter algorithm;frequency modulation;heart ventricle extrasystole;Hilbert vibration decomposition algorithm;modified recursive least square algorithm;noise reduction;normalized sign least mean square algorithm;power line interference noise;priority journal;QRS complex;recording;signal noise ratio;signal processing;simulation;wavelet transformation |
Issue Date: | 2018 |
Publisher: | Elsevier Ltd |
Citation: | Sharma, R. R., & Pachori, R. B. (2018). Baseline wander and power line interference removal from ECG signals using eigenvalue decomposition. Biomedical Signal Processing and Control, 45, 33-49. doi:10.1016/j.bspc.2018.05.002 |
Abstract: | In this paper, a novel method is proposed for baseline wander (BW) and power line interference (PLI) removal from electrocardiogram (ECG) signals. The proposed methodology is based on the eigenvalue decomposition of the Hankel matrix. It has been observed that the end-point eigenvalues of the Hankel matrix formed using noisy ECG signals are correlated with BW and PLI components. We have proposed a methodology to remove BW and PLI noise by eliminating eigenvalues corresponding to noisy components. The proposed concept uses one-step process for removing both BW and PLI noise simultaneously. The proposed method has been compared with other existing methods using performance measure parameters namely output signal to noise ratio (SNRout), and percent root mean square difference (PRD). Simulation results validate the better performance of the proposed method than compared methods at different noise levels. The proposed method is suitable for preprocessing of ECG signals. © 2018 Elsevier Ltd |
URI: | https://doi.org/10.1016/j.bspc.2018.05.002 https://dspace.iiti.ac.in/handle/123456789/5827 |
ISSN: | 1746-8094 |
Type of Material: | Journal Article |
Appears in Collections: | Department of Electrical Engineering |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
Altmetric Badge: