Physiological Signal Classification with Artificial Neural Networks - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2003

Physiological Signal Classification with Artificial Neural Networks

Nizar Kerkeni
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Laurent Bougrain
Rafik Braham
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Mohamed Dogui
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Résumé

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.
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Dates et versions

inria-00099795 , version 1 (26-09-2006)

Identifiants

  • HAL Id : inria-00099795 , version 1

Citer

Nizar Kerkeni, Mohamed Hedi Bédoui, Laurent Bougrain, Rafik Braham, Mohamed Dogui. Physiological Signal Classification with Artificial Neural Networks. Computational Engineering in Systems Applications - CESA'2003, 2003, Lille, France, 4 p. ⟨inria-00099795⟩
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