Digital processing of EEG signals

The digitization of electroencephalogram (EEG) signal data is the essential first step in using computers to analyse and manipulate EEG data. EEG signals are inherently complicated due to their nonGaussian, nonstationary, and often nonlinear nature as shown by most of the articles of this special issue. On top of that, the small amplitude of these signals reinforce their sensitivity to various artifacts and noise sources. The aim of this special issue is to shed light onto the recent digital techniques for processing EEG signals ranging from storage and artifact removal to event detection/classification and prediction issues.