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Antoine NONCLERCQ


coordonnées


Ecole polytechnique de Bruxelles
Antoine NONCLERCQ
tel 02 650 30 86, Antoine.Nonclercq@ulb.ac.be
http://beams.ulb.ac.be
Campus du Solbosch
CP165/56, avenue F.D. Roosevelt 50, 1050 Bruxelles




unités de recherche


Traitement des Signaux (LIST/TS) [Signal Processing Group] (LIST/TS)



projets


Détection et prédiction de crises d'épilepsie [On-line detection and prediction of epileptic seizures]
L'objectif de cette recherche est de modéliser à l'aide de circuits oscillants l'activité électrique neuronale et son comportement pathologique lors des crises d'épilepsie. Cela permettra de mieux comprendre le processus qui amène à la crise et de connaître les paramètres qui sont les marqueurs du changement dans la dynamique de l'EEG. Des algorithmes de détection et de prédiction seront alors développés sue base des informations issues de la modélisation. [Electroencephalography is a useful tool for physicians. It can be used for diagnostic purposes in many brain's pathologies as epilepsy, sleep troubles, etc. Epilepsy is the most current pathology in this field and concerns about 1% of the population. One of the characteristics of epilepsy is the presence of repetitive seizures. Clinically, these seizures can take different forms: from muscular moves to critical convulsions called 'Grand Mal' or tonic-clonic seizure. In EEG signals, an epileptic seizure is characterized by high-voltage and rhythmic EEG waveforms. High-voltage signals show a phenomenon of high synchronous activities of the brain or a part of it. Epilepsy can be focal (or partial) if the seizure is reduced to a part of the brain, called the focus. If the entire brain is affected, the epilepsy is said to be generalized. The automatic detection of epileptic seizure is an important purpose for specialist's diagnostic, because it could save the specialist time by pointing out the seizure periods. Furthermore, another interesting challenge in the field of EEG signal processing is the ability of predicting a seizure. It could enable in the future to avoid seizures of the patients by means of different techniques. Several linear and nonlinear features have been investigated in the literature. But at the present time, it's difficult to say if an epileptic seizure is reliably predictable. In the literature, different kinds of models have been proposed to simulate EEG signals. They use neurophysiologic mechanisms and are called 'mean-field models' because of their macroscopic approach. These models are able to represent epileptic-like EEG signals as well as normal EEG signals. They strongly suggest that epileptic activity is related with the instability or quasi-instability of the system leading to rhythmic activities. Investigating this feature of epileptic process in EEG signals could permit to better understand this process and to provide a feature for characterizing the epileptic seizure in computer-based monitoring of EEG. ]



disciplines et mots clés déclarés


Electromagnétisme - analyse du signal Ingénierie biomédicale Sciences de l'ingénieur

crises d'épilepsie détection et prédiction traitement du signal eeg