Abstract
This work is focused on the study of the organization of the SEEG signals during epileptic seizures. We propose a fuzzy algorithm approach for the classification of the interesting signals. This new classification method use a non linear regression coefficient and is able to provide a relevant brain area structures organisation and to bring out epileptogenic networks pertinent elements. The method gives good results when applied to SEEG signals.
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© 2011 Springer-Verlag Berlin Heidelberg
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Kinié, A., Ndiaye, M. (2011). Fuzzy Algorithm for SEEG Classification. In: Jobbágy, Á. (eds) 5th European Conference of the International Federation for Medical and Biological Engineering. IFMBE Proceedings, vol 37. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23508-5_46
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DOI: https://doi.org/10.1007/978-3-642-23508-5_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23507-8
Online ISBN: 978-3-642-23508-5
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