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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Methodology for Epileptic Episode Detection Using Complexity-Based Features
verfasst von : Jorge Andrés Gómez García, Carolina Ospina Aguirre, Edilson Delgado Trejos, Germán Castellanos Dominguez
Erschienen in: New Challenges on Bioinspired Applications
Verlag: Springer Berlin Heidelberg
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Epilepsy is a neurological disease with a high prevalence on human beings, for which an accurate diagnosis remains as an essential step for medical treatment. Making use of pattern recognition tools is possible to design accurate automatic detection systems, capable of helping medical diagnostic. The present work presents an automatic epileptic episode methodology, based on complexity analysis where 3 classical nonlinear dynamic based features are used in conjunction with 3 regularity measures. k-nn and Support Vector Machines are used for classification. Results, superior to 98% confirm the discriminative ability of the presented methodology on epileptic detection labours.