INVESTIGATION OF ICA ALGORITHMS FOR FEATURE EXTRACTION OF EEG SIGNALS IN DISCRIMINATION OF ALZHEIMER DISEASE
Jordi Solé‐Casals, François Vialatte, Zhe Sage Chen, Andrzej Cichocki · 2008
In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.