Identifying seizure onset zone from electrocorticographic recordings: A machine learning approach based on phase locking value.

Journal: Seizure
Published Date: Oct 1, 2017

Abstract

PURPOSE: Using a novel technique based on phase locking value (PLV), we investigated the potential for features extracted from electrocorticographic (ECoG) recordings to serve as biomarkers to identify the seizure onset zone (SOZ).

Authors

  • Bahareh Elahian
    Department of Electrical and Computer Engineering, University of Memphis, Memphis, TN, USA. Electronic address: belahian@memphis.edu.
  • Mohammed Yeasin
    Department of Electrical and Computer Engineering, University of Memphis, Memphis, TN, USA.
  • Basanagoud Mudigoudar
    Department of Pediatrics, Division of Pediatric Neurology, University of Tennessee Health Science Center, Le Bonheur Comprehensive Epilepsy Program, Le Bonheur Children's Hospital, Memphis, TN, USA; Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA.
  • James W Wheless
    Department of Pediatrics, Division of Pediatric Neurology, University of Tennessee Health Science Center, Le Bonheur Comprehensive Epilepsy Program, Le Bonheur Children's Hospital, Memphis, TN, USA; Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA.
  • Abbas Babajani-Feremi
    Department of Pediatrics, Division of Clinical Neurosciences, University of Tennessee Health Science Center, Memphis, TN, USA; Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA; Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA. Electronic address: ababajan@uthsc.edu.

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