SEIZURE FORECASTING AND THE PREICTAL STATE IN CANINE EPILEPSY

Varatharajah Y1, Iyer RK1, Berry BM2, Worrell GA2, Brinkmann BH2.

The ability to predict seizures may enable patients with epilepsy to better manage their medications and activities, potentially reducing side effects and improving quality of life. Forecasting epileptic seizures remains a challenging problem, but machine learning methods using intracranial electroencephalographic (iEEG) measures have shown promise. A machine-learningbased pipeline was developed to process iEEG recordings and generate seizure warnings. Results support the ability to forecast seizures at rates greater than a Poisson random predictor for all feature sets and machine learning algorithms tested. In addition, subject-specific neurophysiological changes in multiple features are reported preceding lead seizures, providing evidence supporting the existence of a distinct and identifiable preictal state.

Int J Neural Syst. 2017 Feb;27(1):1650046. Epub 2016 Jun 14.

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