In this paper, a novel methodology that automatically identifies segments of EEG recordings with epileptic activity based on multi-rate adaptive filter banks is presented. As an advantage, the proposed approach accurately tracks parameters variability in the specific frequency band of each filter according to its energy in the spectrogram. To this end, the Shannon energy is used as information criteria for filter variability computed over the time-frequency information of the EEG data. Hence, both time and frequency data variability are