Key result
The VMD-DWT approach outperformed the conventional EMD-DWT for ECG signal denoising, although a non-local means reference technique provided better results than VMD-DWT.
For ECG signal denoising, a non-local means approach outperforms both VMD-DWT and EMD-DWT hybrid models.
Non-local means may be preferred for ECG denoising; leaves open whether VMD-DWT hybrids merit further clinical validation.
Hybrid denoising models based on combining empirical mode decomposition (EMD) and discrete wavelet transform (DWT) were found to be effective in removing additive Gaussian noise from electrocardiogram (ECG) signals. Recently, variational mode decomposition (VMD) has been proposed as a multiresolution technique that overcomes some of the limits of the EMD. Two ECG denoising approaches are compared. The first is based on denoising in the EMD domain by DWT thresholding, whereas the second is based on noise reduction in the VMD domain by DWT thresholding. Using signal-to-noise ratio and mean of squared errors as performance measures, simulation results show that the VMD-DWT approach outperforms the conventional EMD-DWT. In addition, a non-local means approach used as a reference technique provides better results than the VMD-DWT approach.
No takes yet. Share an insight, caveat, or question.
Salim Lahmiri (2014) studied ECG signal denoising. Variational mode decomposition (VMD) with DWT thresholding vs. Empirical mode decomposition (EMD) with DWT thresholding was evaluated on Signal-to-noise ratio and mean of squared errors. The VMD-DWT approach outperformed the conventional EMD-DWT for ECG signal denoising, although a non-local means reference technique provided better results than VMD-DWT.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: