Abstract Many studies have focused on the nonlinear analysis of electroencephalography mainly for the characterization of epileptic brain states. The spatial and temporal dynamics of the epileptogenic process is still not clear completely especially the most challenging aspects of epileptology which is the anticipation of the seizure. Despite all the efforts we still don’t know how and when and why the seizure occurs. However actual studies bring strong evidence that the interictal-ictal state transition is not an abrupt phenomena. Findings also indicate that it is possible to detect a preseizure phase. We will study the patients admitted to the epilepsy monitoring unit for the purpose of recording their seizures. These patients have their EEG signal recorded 24 hours a day for several days until they have enough number of seizures to determine eligibility for seizure surgery. Thus, preictal, ictal, and post ictal electroencephalography recordings are available on such patients for analysis. We propose to use wavelet analysis in order to investigate a case study of the electroencephalography signal and determine the localization of the seizure and its characteristics.

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[14] Williams W., Zaveri H., and Sckellares C., Time-Frequency Analysis of Electrophysiology Signals in Epilepsy, IEEE Engineering in Medicine and Biology , vol. 14, no. 2, pp. 133-43, 1995. Nisrine Sinno received her PhD in Electroniques from the National Polytechnic Institute of Grenoble (INPG /ENSERG) in 1983. Her Research work consists of circuits simulation and modelling, linear, nonlinear, stochastic approach, performance of numerical analysis in simulating networks, and epileptic signals analysis using the wavelet packets approach. Kifah Tout is professor of computer science at the Lebanese University, Faculty of Sciences I, Beirut. He holds a PhD degree in computer science from Loughborough University of Technology, UK, 1991. He was technical director for the European Projects Parallel Programming Environment for Genetic Algorithms (PAPAGENA) and Heterogeneous Application Generator Standard Architecture for the use of Neural Networks (HANSA) with collaboration from European partners such as Thorn EMI crl (England), Brainware (Germany), Olivetti Group (Italy), University College London, CAP Volmac (Holland), IMAG (France), German Computer Research Centre (Germany), and Institute for Cybernetic and Systems Theory (Germany). He is a member of IEEE, ACM, and EU Team of Experts. Dr. Tout currently supervises two PhD students in knowledge management and indexing and searching multimedia content.