Design and implementation of EEMD-assisted ICA joint denoising scheme for ECG signals

Independent Component Analysis (ICA) algorithm is a signal processing method for solving blind source separation(BSS) problem, which can remove noises in observed signals and obtain original signals. This paper designs and implements an EEMD-assisted ICA joint denoising scheme for ECG signals. Firstly, Ensemble Empirical Mode Decomposition (EEMD) is used to perform noise-assisted data analysis on ECG signals, completing pre-denoising of ECG signals and pre-processing for subsequent ICA analysis. Next, to more thoroughly remove noises in ECG signals, ICA separates independent components from pre-denoised signals. Finally, signal reconstruction restores original ECG signals, so as to realize ECG denoising. Experimental results show that the scheme can effectively remove common noises, and get clean ECG signals, which lay a good foundation for accurate diagnosis of heart patients.