Classification of epileptic motor manifestations using inertial and magnetic sensors

Authors:
Guillaume Becq;Stéphane Bonnet;Lorella Minotti;Michel Antonakios;Régis Guillemaud;Philippe Kahane
Affiliations:
Grenoble Institut des Neurosciences, Inserm U 836-UJF-CEA-CHU, University Hospital Center of Grenoble, BP 217, 38043 Grenoble cedex 9, France and Gipsa-lab, Grenoble INP, CNRS, UJF, Stendhal, Depa ...;CEA/Leti/DTBS/LE2S, 17 rue des martyrs, 38054 Grenoble cedex, France;Grenoble Institut des Neurosciences, Inserm U 836-UJF-CEA-CHU, University Hospital Center of Grenoble, BP 217, 38043 Grenoble cedex 9, France;CEA/Leti/DTBS/LE2S, 17 rue des martyrs, 38054 Grenoble cedex, France;CEA/Leti/DTBS/LE2S, 17 rue des martyrs, 38054 Grenoble cedex, France;Grenoble Institut des Neurosciences, Inserm U 836-UJF-CEA-CHU, University Hospital Center of Grenoble, BP 217, 38043 Grenoble cedex 9, France
Venue:
Computers in Biology and Medicine
Year:
2011

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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.