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  • Letters to the Editor
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Prediction of epileptic seizures: are nonlinear methods relevant?

Nature Medicine volume 9, pages 241–242 (2003)Cite this article

To the editor

Epilepsy is one of the most common serious neurological disorders, affecting 1% of the population at some time. Reliable and robust detection of seizure precursors would improve the quality of life of many epilepsy sufferers. It is likely that the processes underlying the electroencephalogram (EEG) signal are nonlinear1,2, but there is little, if any, concrete evidence that such signals reflect deterministic chaos. Regardless of fundamental dynamics, the relevant operational question is whether or not the information reflected in a proposed test statistic justifies its use (given its complexity). Can a complicated, novel and potentially nonlinear method systematically out-perform traditional 'linear' methods such as analysis of variance, or provide independent and complementary precursor information?

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Figure 1: Results based upon the database investigated by Martinerie et al.4.

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Author information

Authors and Affiliations

  1. Mathematical Institute, University of Oxford, Oxford, UK

    Patrick E. McSharry & Leonard A. Smith

  2. Department of Engineering, University of Oxford, Oxford, UK

    Patrick E. McSharry & Lionel Tarassenko

  3. Centre for the Analysis of Time Series, London School of Economics, London, UK

    Leonard A. Smith

Authors
  1. Patrick E. McSharry
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  2. Leonard A. Smith
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  3. Lionel Tarassenko
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Correspondence to Patrick E. McSharry.

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McSharry, P., Smith, L. & Tarassenko, L. Prediction of epileptic seizures: are nonlinear methods relevant?. Nat Med 9, 241–242 (2003). https://doi.org/10.1038/nm0303-241

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