Automated classification of five seizure onset patterns from intracranial electroencephalogram signals.

Journal: Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Published Date: Mar 3, 2020

Abstract

OBJECTIVE: The electroencephalographic (EEG) signals contain information about seizures and their onset location. There are several seizure onset patterns reported in the literature, and these patterns have clinical significance. In this work, we propose a system to automatically classify five seizure onset patterns from intracerebral EEG signals.

Authors

  • Navaneethakrishna Makaram
    Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.
  • Nicolás von Ellenrieder
    Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.
  • Hideaki Tanaka
    Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada; Department of Neurosurgery, Fukuoka University Hospital, Fukuoka City, Japan.
  • Jean Gotman
    Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.

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