With the growing opportunities of laboratories and measurement techniques, cognitive science attracts many researchers interest from other branches of science. In the literature, lack of studies related to the brain's responsiveness against the olfactory stimuli has been the main source of motivation for our work on this issue. In this thesis, it is examined by means of time-dependent wavelet entropy of Electroencephalographic (EEG) signals which is collected from individuals that how olfactory and trigeminal effective odor stimuli affects responsiveness of the brain. Significance and meaningfulness of the results are shown with statistical tests of average entropy in the discrete time windows. Due to its nature of small amplitude in comparison with ongoing EEG activity, it’s hard to observe the components of olfactory evoked potentials and trigeminal evoked potentials. In order to separate these components from ongoing EEG, different signal processing techniques have been employed in this thesis. And, findings from these techniques have been conveyed to statistical tests to determine the most suitable technique for that purpose. Additionally, a novel smell performance identification metric have been offered for clinical studies that is not affected by basal activity of brain and subjective review, for objective assessment of smell performance. Statistical test result have shown that, results of this technique which is performed on 19 participants, and their TDI scores obtained from Sniffin’ Stick test battery, are in a strong correlation.