  The analysis of electrophysiological signal of scalp: EEG
(electroencephalography), MEG (magnetoencephalography) and depth (intracerebral
EEG) IEEG is a way to delimit epileptogenic zone (EZ). These epileptic signals
present two different activities (oscillations and spikes) which can be
overlapped in the time frequency plane. Automatic recognition of epileptic
seizure occurrence needs several preprocessing steps. In this study, we
evaluated two filtering techniques: the stationary wavelet transforms (SWT) and
the Despikifying in order to extract pre ictal gamma oscillations (bio markers
of seizure build up). Then, we used a temporal basis set of Jmail et al 2017 as
a preprocessing step to evaluate the performance of both technique. Moreover,
we used time-frequency and spatio-temporal mapping of simulated and real data
for both techniques in order to predict seizure build up (in time and space).
We concluded that SWT can detect the oscillations, but Despikyfying is more
robust than SWT in reconstructing pure pre ictal gamma oscillations and hence
in predicting seizure build up.
