Reconstruction of Electroncephalogram Brain Maps by Incorporating the Blind Source Separation Concept

Electroencephalogram (EEG) brain maps provide useful and reliable neurodiagnostic information. Accurate reconstruction of the data requires an efficient separation of the electrode signals. Although autoregressive (AR) spectrum estimation highly refines the signals, it cannot remove the effect of adjacent electrode signals. This report describes an efficient blind signal separation (BSS) method. The algorithm identifies the coefficients of an adaptive FIR filter by minimization of a cost function in terms of the corresponding fourth-order cumulants. Applying this method, the quality of the results is far superior to the traditional methods.