Method for obtaining an indicator of presence for Alzheimer's disease using EEG signals

A method for obtaining an indicator of presence for Alzheimer's disease using EEG signals from a subject, comprising the steps: obtaining an EEG signal of a subject; applying an analysis filter bank for processing the obtained EEG signal into a plurality, m, of subband signals, Xm(n); applying the module to each subband signal, to obtain the module of each subband signal, |xm(n)]; applying a logarithm to each subband signal's module, |Xm(n)], to obtain the logarithmic magnitude of each subband signal; applying synthesis filter bank to each subband signal for reconstructing a corresponding subband signal, ym(n); applying the module to the reconstructed subband signal, ym(n), to obtain an output subband signal, x(n); calculating a set of distance functions for obtaining distances between output subband signals, x'(n); feeding the calculated set of distances to a pre-trained machine learning classifier to obtain a classification score: wherein the classification score is indicative for the Alzheimer's disease presence.