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Classification of epileptic motor manifestations using inertial and magnetic sensors

Abstract : In order to characterize objectively the succession of movements observed during motor seizures, inertial and magnetic sensors were placed on epileptic patients. Video recordings synchronized with motion recordings were analyzed visually during seizures and divided, for each limb, into events corresponding to different classes of motor manifestations. For each classified event, features were extracted and a subset selection was automated using artificial neural networks. The best artificial neural network was simulated on whole recordings to generate a stereotypic evolution of motor manifestations that we called motorograms. It is shown that motorograms can point out seizure movements and emphasize epileptic patterns.
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Contributor : Guillaume Becq Connect in order to contact the contributor
Submitted on : Friday, February 4, 2011 - 1:39:08 PM
Last modification on : Tuesday, October 19, 2021 - 11:22:42 PM




Guillaume Becq, Stéphane Bonnet, Lorella Minotti, Michel Antonakios, Régis Guillemaud, et al.. Classification of epileptic motor manifestations using inertial and magnetic sensors. Computers in Biology and Medicine, Elsevier, 2011, 41 (1), pp.46-55. ⟨10.1016/j.compbiomed.2010.11.005⟩. ⟨hal-00563232⟩



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