Abstract: An electroencephalographic signal processing method allows the stages of sleep to be determined in real time as an EEG signal is being picked up. The EEG signal is divided into time segments of the same length; each signal segment is sampled digitally to obtain successive blocks of N samples; for each block i, M standardized correlation coefficients R.sub.i,k are determined, M being much far smaller than N; for each block i, the distances D(i,j) between the coefficients R.sub.i,k of the current block and the coefficients R.sub.j,k of the centers of gravity of existing classes j are calculated; the minimum D(i,p) of distances D(i,j) is selected; block i is assigned to class p and the center of gravity of the class is updated if D(i,p) is below a given threshold, while a new class is created if D(i,p) is above the given threshold; and each class is assigned to the closest stage from the standpoint of energy distribution beween frequency bands.