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Cited by 450Epilepsy research and treatmentEEG and Brain-Computer InterfacesSeismology and Earthquake Studies

Seizure prediction – ready for a new era

Open access
Kuhlmann, Levin, Lehnertz, Klaus, Richardson, Mark P., Schelter, Björn, Zaveri, Hitten P.·2018·Nature Reviews Neurology
DOI 10.1038/s41582-018-0055-2
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Abstract

Epilepsy is a common disorder characterized by recurrent seizures. An overwhelming majority of people with epilepsy regard the unpredictability of seizures as a major issue. More than 30 years of international effort have been devoted to the prediction of seizures, aiming to remove the burden of unpredictability and to couple novel, time-specific treatment to seizure prediction technology. A highly influential review published in 2007 concluded that insufficient evidence indicated that seizures could be predicted. Since then, several advances have been made, including successful prospective seizure prediction using intracranial EEG in a small number of people in a trial of a real-time seizure prediction device. In this Review, we examine advances in the field, including EEG databases, seizure prediction competitions, the prospective trial mentioned and advances in our understanding of the mechanisms of seizures. We argue that these advances, together with statistical evaluations, set the stage for a resurgence in efforts towards the development of seizure prediction methodologies. We propose new avenues of investigation involving a synergy between mechanisms, models, data, devices and algorithms and refine the existing guidelines for the development of seizure prediction technology to instigate development of a solution that removes the burden of the unpredictability of seizures.

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Research works printed but not linked: 28

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Authors
Kuhlmann, L., Lehnertz, K., Richardson, M. P., Schelter, B., & Zaveri, H. P.
Affiliations
  • The University of Melbourne (AU)
  • University of Bonn (DE)
  • King's College London (GB)
  • University of Aberdeen (GB)
  • Yale University (US)
Corresponding author
Lehnertz, Klaus
ORCID
Venue
Nature Reviews Neurology
Publisher
Springer Science and Business Media LLC
Published
2018-08-21
Volume
14
Issue
10
Pages
618-630
ISSN
  • 1759-4758 (ISSN-L)
  • 1759-4766
DOI
10.1038/s41582-018-0055-2
OpenAlex
W2888598199
Cited by
450
References
223
Citations by year
2026: 39 · 2025: 53 · 2024: 70 · 2023: 64 · 2022: 61 · 2021: 73 · 2020: 53 · 2019: 32 · 2018: 4
FWCI
6.16
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (tdm)
Locations
  • Nature Reviews Neurology (publishedVersion)
  • PubMed (publishedVersion)
  • Aberdeen University Research Archive (Aberdeen University) (submittedVersion)
  • Research Portal (King's College London) (submittedVersion)
  • Swinburne figshare (Swinburne University of Technology) (submittedVersion)
Funders
  • James S. McDonnell Foundation (220020419)
  • Medical Research Council
  • National Health and Medical Research Council (1130468)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Epilepsy research and treatment
  • Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
  • Physical Sciences › Computer Science › Artificial Intelligence › Seismology and Earthquake Studies
Keywords
seizure prediction, epilepsy, intracranial EEG, EEG database, seizure mechanisms, seizure burden
MeSH terms
Electroencephalography, Epilepsy, Humans, Seizures, Databases, Factual, Monitoring, Ambulatory

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