Nonictal electroencephalographic measures for the diagnosis of functional seizures.

Journal: Epilepsia
Published Date: Sep 10, 2024

Abstract

OBJECTIVE: Functional seizures (FS) look like epileptic seizures but are characterized by a lack of epileptic activity in the brain. Approximately one in five referrals to epilepsy clinics are diagnosed with this condition. FS are diagnosed by recording a seizure using video-electroencephalography (EEG), from which an expert inspects the semiology and the EEG. However, this method can be expensive and inaccessible and can present significant patient burden. No single biomarker has been found to diagnose FS. However, the current limitations in FS diagnosis could be improved with machine learning to classify signal features extracted from EEG, thus providing a potentially very useful aid to clinicians.

Authors

  • Chloe H L Hinchliffe
    Centre for Biomedical Engineering, School of Mechanical Engineering Sciences, University of Surrey, Guildford, UK.
  • Mahinda Yogarajah
    Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, National Hospital for Neurology and Neurosurgery, University College London Hospital, Epilepsy Society, London, UK.
  • Samia Elkommos
    Atkinson Morley Regional Neuroscience Centre, St. George's Hospital, London, UK.
  • Hongying Tang
    Department of Computer Science, University of Surrey, Guildford, UK.
  • Daniel Abasolo
    Centre for Biomedical Engineering, Department of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, United Kingdom.

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