Physiological Signal Classification with Artificial Neural Networks
| Autor: | Kerkeni, Nizar, Bédoui, Mohamed Hedi, Bougrain, Laurent, Braham, Rafik, Dogui, Mohamed |
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| Přispěvatelé: | Laboratoire des Technologies de l'Information et de la Modélisation [Casablanca] (TIM), Faculté des Sciences Ben M'sik [Casablanca], Université Hassan II [Casablanca] (UH2MC)-Université Hassan II [Casablanca] (UH2MC), Neuromimetic intelligence (CORTEX), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2003 |
| Předmět: | |
| Zdroj: | Computational Engineering in Systems Applications-CESA'2003 Computational Engineering in Systems Applications-CESA'2003, 2003, Lille, France, 4 p |
| Popis: | Colloque avec actes et comité de lecture. nationale.; National audience; A connectionist tool to help diagnose physiological signal, the Somatosensory Evoked Potentials (SEP), is presented. It is designed to be used in functional neurophysiological exploration. The tool should decide whether the signal is normal or pathological according to the inferior limbs SEP recording of an adult population. The obtained results (with a rate of success of 84%) allow us to think how to enlarge the application field of our tool to other evoked potentials and mainly to enlarge the data by the acquisition of SEP at different recording sites to locate the pathology. |
| Databáze: | OpenAIRE |
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