Document Type

Conference Paper

Publication Date


Publication Title

Selected Papers and Presentations Presented at MODSIM World 2010 Conference & Expo



Conference Name

MODSIM World 2010 Conference & Expo, October 13-15, 2010, Hampton, Virginia


In this paper we developed a wavelet neural network. (WNN) algorithm for Electroencephalogram (EEG) artifact removal without electrooculographic (EOG) recordings. The algorithm combines the universal approximation characteristics of neural network and the time/frequency property of wavelet. We compared the WNN algorithm with the ICA technique and a wavelet thresholding method, which was realized by using the Stein's unbiased risk estimate (SURE) with an adaptive gradient-based optimal threshold. Experimental results on a driving test data set show that WNN can remove EEG artifacts effectively without diminishing useful EEG information even for very noisy data.


"Distribution/Availability Statement: Unclassified - Unlimited"

Original Publication Citation

Nguyen, H.-A. T., Musson, J., Li, J., McKenzie, F., Zhang, G., Xu, R., Richey, C., & Schnell, T. (2011) EEG artifact removal using a wavelet neural network. In T.E. Pinelli (Ed.), Selected papers and presentations presented at MODSIM World 2010 Conference & Expo (pp. 820-845). NASA Center for Aerospace Information.


0000-0003-0091-6986 (Li)