Om Prakash Yadav 1, Shashwati Ray2, and Yojana Yadav1
1PES Institute of Technology and Management ,Shivamogga,Karnataka, 577204, India 2Bhilai Institute of Technology, Durg, CG,491001, India
Received: August 1, 2020 Accepted: March 28, 2021 Publication Date: June 22, 2021
Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.
An Electrocardiogram (ECG) signal representing the heart’s electrical behaviour is often corrupted by artefacts that may prevent correct diagnosis and hence need to be reduced for better clinical assessment. The first difference total variation that measures variation between consecutive samples of signals has been useful for reducing artefacts from signals. However, for quasi-stationary signals having a weak signal to noise ratio, the method’s performance is not satisfactory. In this paper, the concept of first difference total variation has been utilized to derive combined difference total variation. The algorithm is executed to reduce simulated noise comprising power line interference, baseline wander, and Gaussian noise added to ECG signals. The performance is measured with standard assessment tools, and the results obtained are compared with the other denoising models reported in the recent literature.
Keywords: ECG, First Difference, Total Variation, Majorization-Minimization Optimization
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