Interictal epileptic spikes can reveal important information about the generators of epileptic activity, especially during the pre-surgical investigation of intractable epilepsy. The visual inspection of EEG recordings done by neurologists to collect the spikes is time consuming and might not always be exhaustive, especially regarding spikes of small amplitude. Automatic spike détection saves a lot of the neurologist's time. Exhaustive détection of spikes is even more necessary when thèse events are used in an event related paradigm to detect hemodynamic activity (functional Magnetic Résonance Imaging, Near InfraRed Spectroscopy). In this context, this study proposes a new semi-automatic spike détection approach that aims to make an inventory of ail the spikes in a run accordingly to few samples marked by an experienced neurophysiologist. The method intégrates information from the neurologist about time (duration), space (corrélations between EEG électrodes) and frequencies (spectral characteristcs). Based on Empirical Mode Décomposition (EMD) représentation of the signais, the method is first validated with realistic simulations. We then présent results for three patients for which this algorithm exhibits a large number of spike like activities of small amplitude but similar sources as the samples given by the neurologist.
| Date | 16 Jul 2010 |
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| Original language | French |
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| Awarding Institution | - École de technologie supérieure
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| Supervisor | Jean-Marc Lina (Supervisor) & Jean Gotman (Co-supervisor) |
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Dubarry, A.-S. (Author),
Lina (Supervisor) & Gotman (Co-supervisor),
16 Jul 2010Student thesis: Master's thesis › Master in Engineering: Engineering