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New clustering of the spikes morphology based on dynamic clouds in partial epilepsy

Abstract : The acquisition of EEG signals can be done during days. In this paper, the signals of depth Stereo-Electroencephalography (SEEG) are used. In SEEG signal, several inter-ictal paroxystic events (IPE) are found, they appear between the crises. To analyze their distribution, they should initially be detected by separating them from the basic activity. After the detection step, we implement a clustering process to distinguish IPE or spike according to their morphology. Results of detection and clustering would characterize a link between space-time distribution of IPE and the arrival of the crises. It would be thus a contribution on the diagnosis of the partial epilepsies. © 2016 IEEE.
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https://hal-univ-rennes1.archives-ouvertes.fr/hal-01381262
Contributor : Laurent Jonchère <>
Submitted on : Friday, October 14, 2016 - 11:40:08 AM
Last modification on : Monday, September 24, 2018 - 5:28:02 PM

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O. Khouma, M.L. Ndiaye, I. Diop, A.K. Diop, S.M. Farsi, et al.. New clustering of the spikes morphology based on dynamic clouds in partial epilepsy. 2016 SAI Computing Conference, SAI 2016, Jul 2016, London, United Kingdom. pp.354--360, ⟨10.1109/SAI.2016.7556006⟩. ⟨hal-01381262⟩

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