Abstract

Neurons are the seat of movements of charged particles, which create microcurrents. Thanks to devices such as the EEG and the MEG, these brain electrical waves can be recorded on the surface of the skull. The frequency of these waves reflects the state of alertness and consciousness. The mathematical tools used to study emotions as an electromagnetic signal are diverse. Indeed, electromag- netic waves have been studied from different angles. The mathematical modeling of such a phenomenon leads back to the resolution of the system formed by the equation of Maxwell, Faraday, Gauss and Am- père. For this, we need the theory of the Fourier transformation. However, a study of an EEG graph, will lead a numeritian to be interested in the analysis of a signal and therefore in the theory of the discrete Fourier transformation and its algorithm the fast Fourier transformation. As the brain waves are repre- sented by functions corresponding to small oscillations, it is possible to use the analsye of the wavelet transformation.