论文信息 - Ocular artifacts removal in scalp EEG: combining ICA and wavelett denoising

Ocular artifacts removal in scalp EEG: combining ICA and wavelett denoising

In this communication we present the first results of a project whose goal is to remove artifacts from electroencephalographic epileptic signals. More precisely the present objective is to remove ocular (blinking) artifacts in simulated and real EEG signal using Independent Component Analysis and wavelet denoising algorithms.

Didier Maquin | Rebeca Romo-Vázquez | Radu Ranta | Valérie Louis-Dorr

[1] Eric Moulines,et al. A blind source separation technique using second-order statistics , 1997, IEEE Trans. Signal Process..

[2] Anestis Antoniadis,et al. Wavelet Estimators in Nonparametric Regression: A Comparative Simulation Study , 2001 .

[3] Jean-Francois Cardoso,et al. Eigen-structure of the fourth-order cumulant tensor with application to the blind source separation problem , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[4] Andrzej Cichocki,et al. Second Order Nonstationary Source Separation , 2002, J. VLSI Signal Process..

[5] Joep J. M. Kierkels,et al. A model-based objective evaluation of eye movement correction in EEG recordings , 2006, IEEE Transactions on Biomedical Engineering.

[6] I. Johnstone,et al. Adapting to Unknown Smoothness via Wavelet Shrinkage , 1995 .

[7] Te-Won Lee,et al. Independent Component Analysis , 1998, Springer US.

[8] Matthew T. Sutherland,et al. Blind source separation can recover systematically distributed neuronal sources from 'resting' EEG , 2006 .

[9] Soo-Young Lee. Blind Source Separation and Independent Component Analysis: A Review , 2005 .

[10] A. Cichocki,et al. Robust whitening procedure in blind source separation context , 2000 .

[11] F. Wendling,et al. Automatic lateralization of temporal lobe epilepsy based on scalp EEG , 2006, Clinical Neurophysiology.