Eigenbrains and Eigentensorbrains: Parsimonious bases for EEG biometrics
Two novel parsimonious EEG representations proposed for biometric recognition. Performance evaluated on EEG data taken in two distinct sessions from 30 subjects. Analysis of the discriminability of distinct EEG sub-bands, with several classifiers. LDA improves the performance if applied to either ETB or EB representations. For recognition, ETB projections better than EB, EC resting conditions better than EO.
eeg biometrics brain waves pca mpca tensor analysis