A review of ECG signal filtering approaches

Anas Fouad Ahmed 1, * and Mohammed K Al-Obaidi 2

1 Electrical Engineering, College of Engineering, Al-Iraqia University, Baghdad, Iraq.
2 Department of Computer Engineering, College of Engineering, Al-Iraqia University, Baghdad, Iraq.
 
Review Article
Global Journal of Engineering and Technology Advances, 2022, 11(03), 093–097.
Article DOI: 10.30574/gjeta.2022.11.3.0099
Publication history: 
Received on 17 May 2022; revised on 23 June 2022; accepted on 25 June 2022
 
Abstract: 
An electrocardiogram (ECG) quantifies the electrical activity of the heart to screen for different heart diseases, although it can be impacted by noise. ECG signal filtering is a crucial pre-processing step that reduces noise and emphasizes the characteristic waves in ECG data. In real-world applications, the ECG signal is contaminated by different types of noise. Separating the desired signal from noises produced by artifacts such as muscle noise, power line interference (PLI), baseline wandering (BW), and motion artifacts (MA) is a complicated task. In this paper, a quick review of various ECG signal denoising methods is introduced.
 
Keywords: 
Electrocardiogram; Power Line Interference; Filtering Techniques; Discrete Wavelet Transform; MSE
 
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