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Enhancement and Analysis of ECG signals using Combined Difference Total Variation Optimization

摘要


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.

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