A Survey on the Performance Analysis of WT, PF, EMD & EEMD Methods used in ECG Signal Processing

A noiseless ECG identification technology is an emerging new biometric modality. Different techniques for de-noising of ECG signal are prevalent in recent literatures such as Particle Filter (PF), wavelet transforms (WT), Empirical Mode Decomposition (EMD) & Ensemble-EMD Method. In view of the fact that Analysis of ECG signals becomes difficult to inspect the cardiac activity in the presence of Noise signals. So, de-noising of ECG signal is extremely important to prevent misinterpretation of patient’s cardiac activity which can lead to wrong diagnosis and further to death. This paper is surveying a comparison on the performance of the Particle Filter (PF), wavelet transforms (WT) and Empirical Mode Decomposition (EMD) & Ensemble EMD methods in context of denoising of an electrocardiogram (ECG) signal. Analysis of the paper provides us the way of selecting best de-noising technique of ECG signal based on the numerical value in terms of SNR and RMSE. The study is limited to signals corrupted by additive white Gaussian random noise.