Removal of Structured Noise and Base Line Wander From ECG Signals via LMS Adaptive and Fixed Notch Filter

Kawser Ahammed
Additional contact information
Kawser Ahammed: Lecturer, Department of Electrical and Electronic Engineering, Jatiya Kabi Kazi Nazrul Islam University, Trishal, Mymensingh, Bangladesh

European Journal of Engineering and Technology Research, 2018, vol. 3, issue 8, 12-15

Abstract: This research clearly demonstrates the comparative performance study of Least Mean Square (LMS) adaptive and fixed Notch filter in terms of simulation results and different performance parameters (mean square error, signal to noise ratio and percentage root mean square difference) for removing structured noise (50 Hz line interference and its harmonics) and baseline wandering from electrocardiogram (ECG) signal. The ECG samples collected from the PhysioNet ECG-ID database are corrupted by adding structured noise and base line wandering noise. The simulation results and numerical performance analysis of this research clearly show that LMS adaptive filter can remove noise efficiently from ECG signal than fixed notch filter

Keywords: LMS Filter; Fixed Notch Filter; Structured Noise; Base line Wander; ECG; Mean Square Error (MSE); Signal to Noise Ratio (SNR); Percentage Root Mean Square Difference (PRD) (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://eu-opensci.org/index.php/ejeng/article/view/60830 Abstract page (text/html)
https://eu-opensci.org/index.php/ejeng/article/download/60830/11934 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:3:y:2018:i:8:id:60830

DOI: 10.24018/ejeng.2018.3.8.830

Access Statistics for this article

More articles in European Journal of Engineering and Technology Research from European Open Science
Bibliographic data for series maintained by Support ().