A novel hybrid EMD-DWT approach improved ECG denoising compared to the EMD approach alone, achieving a higher Signal to Noise Ratio (10.7181 vs 9.8821) and lower Root Mean Square Error (0.0707 vs 0.0890).
A novel hybrid EMD-DWT denoising technique improves ECG signal quality compared to conventional EMD methods by reducing noise and enhancing signal-to-noise ratio.
Electrocardiogram (ECG) is the most important signal in the biomedical field for the diagnosis of Cardiac Arrhythmia (CA). ECG signal often interrupted with various noises due to non-stationary nature which leads to poor diagnosis. Denoising process helps the physicians for accurate decision making in treatment. In many papers various noise elimination techniques are tried to enhance the signal quality. In this paper a novel hybrid denoising technique using EMD-DWT for the removal of various noises such as Additive White Gaussian Noise (AWGN), Baseline Wander (BW) noise, Power Line Interference (PLI) noise at various concentrations are compared to the conventional methods in terms of Root Mean Square Error (RSME), Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR), Cross-Correlation (CC) and Percent Root Square Difference (PRD). The average values of RMSE, SNR, PSNR, CC and PRD are 0.0890, 9.8821, 14.4464, 0.9872 and 10.9036 for the EMD approach, respectively, and 0.0707, 10.7181, 16.2824, 0.9874 and 10.7245 for the proposed EMD-DWT approach, respectively, by removing AWGN noise. Similarly BW noise and PLI are removed from the ECG signal by calculating the same quality metrics. The proposed methodology has lower RMSE and PRD values, higher SNR, PSNR and CC values than the conventional methods.
Malleswari et al. (Mon,) conducted a other in Cardiac Arrhythmia. EMD-DWT approach vs. EMD approach was evaluated on Denoising performance (RMSE, SNR, PSNR, CC, PRD) for AWGN noise. A novel hybrid EMD-DWT approach improved ECG denoising compared to the EMD approach alone, achieving a higher Signal to Noise Ratio (10.7181 vs 9.8821) and lower Root Mean Square Error (0.0707 vs 0.0890).
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