Electrocardiogram (ECG) signal has a principal role in the diagnosis of diverse kinds of heart diseases. During ECG recording, a variety of noise sources permit to alter the morphology of these signals and result in erroneous interpretations. Denoising of the ECG signal is a great pretreating phase that minimizes the noise for an accurate diagnosis. In this paper, a new hybrid technique based on Variational Mode Decomposition (VMD) and the Average Wavelet Coefficient method (AWC) for ECG signal denoising is presented. The suggested method at first involves the implementation of VMD to the noisy ECG signal for decomposition purposes to gain variational modes, these obtained variational modes are then treated using the AWC technique that permits the computing of the Hurst exponent of all variational modes. Lastly, the denoised ECG signal is reconstructed by summing up all the denoised variational modes, after a thresholding operation, barring parasitical signal elements. Experiments implementing the MIT-BIH databases are used to approve and evaluate the suggested technique. The experimental finding indicate that the proposed approach recovers ECG signals from noisy data samples efficiently.
Citation
Zahia nabi ,
,(2022), An appropriate hybrid technique for ECG signal denoising based on variational mode decomposition and average wavelet coefficient method,1st International Conference on Engineering, Natural and Social Sciences ICENSOS 2022,Turquie
