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Seizure prediction for therapeutic devices: A review.

Publication ,  Journal Article
Gadhoumi, K; Lina, J-M; Mormann, F; Gotman, J
Published in: Journal of neuroscience methods
February 2016

Research in seizure prediction has come a long way since its debut almost 4 decades ago. Early studies suffered methodological caveats leading to overoptimistic results and lack of statistical significance. The publication of guidelines addressing mainly the question of performance evaluation and statistical validation in seizure prediction helped revising the status of the field. While many studies failed to prove that above chance prediction is possible by applying these guidelines, other studies were successful. Methods based on EEG analysis using linear and nonlinear measures were reportedly successful in detecting preictal changes and using them to predict seizures above chance. In this review, we present a selection of studies in seizure prediction published in the last decade. The studies were selected based on the validity of the methods and the statistical significance of performance results. These results varied between studies and many showed acceptable levels of sensitivity and specificity that could be appealing for therapeutic devices. The relatively large prediction horizon and early preictal changes reported in most studies suggest that seizure prediction may work better in closed loop seizure control devices rather than as seizure advisory devices. The emergence of a large database of annotated long-term EEG recordings should help prospective assessment of prediction methods. Some questions remain to be addressed before large clinical trials involving seizure prediction can be carried out.

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Published In

Journal of neuroscience methods

DOI

EISSN

1872-678X

ISSN

0165-0270

Publication Date

February 2016

Volume

260

Start / End Page

270 / 282

Related Subject Headings

  • Sensitivity and Specificity
  • Seizures
  • Reproducibility of Results
  • Prognosis
  • Pattern Recognition, Automated
  • Neurology & Neurosurgery
  • Humans
  • Equipment Failure Analysis
  • Equipment Design
  • Electroencephalography
 

Citation

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Gadhoumi, K., Lina, J.-M., Mormann, F., & Gotman, J. (2016). Seizure prediction for therapeutic devices: A review. Journal of Neuroscience Methods, 260, 270–282. https://doi.org/10.1016/j.jneumeth.2015.06.010
Gadhoumi, Kais, Jean-Marc Lina, Florian Mormann, and Jean Gotman. “Seizure prediction for therapeutic devices: A review.Journal of Neuroscience Methods 260 (February 2016): 270–82. https://doi.org/10.1016/j.jneumeth.2015.06.010.
Gadhoumi K, Lina J-M, Mormann F, Gotman J. Seizure prediction for therapeutic devices: A review. Journal of neuroscience methods. 2016 Feb;260:270–82.
Gadhoumi, Kais, et al. “Seizure prediction for therapeutic devices: A review.Journal of Neuroscience Methods, vol. 260, Feb. 2016, pp. 270–82. Epmc, doi:10.1016/j.jneumeth.2015.06.010.
Gadhoumi K, Lina J-M, Mormann F, Gotman J. Seizure prediction for therapeutic devices: A review. Journal of neuroscience methods. 2016 Feb;260:270–282.
Journal cover image

Published In

Journal of neuroscience methods

DOI

EISSN

1872-678X

ISSN

0165-0270

Publication Date

February 2016

Volume

260

Start / End Page

270 / 282

Related Subject Headings

  • Sensitivity and Specificity
  • Seizures
  • Reproducibility of Results
  • Prognosis
  • Pattern Recognition, Automated
  • Neurology & Neurosurgery
  • Humans
  • Equipment Failure Analysis
  • Equipment Design
  • Electroencephalography