EEG Ocular Artefacts and Noise Removal
Rebeca Romo Vázquez, Radu Ranta, Valérie Louis-Dorr, Didier Maquin · Conference proceedings · 2007
The general framework of this research is the pre-processing of the electroencephalographic (EEG) signals. The goal of this paper is to compare several combinations of wavelet denoising (WD) and independent component analysis (ICA) algorithms for noise and artefacts removal. These methods are tested on simulated EEG, using different evaluation criteria. According to our results, the most effective method consists in source separation by SOBI-RO [1], followed by wavelet denoising by SURE thresholding [2].