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Forecasting cycles of seizure likelihood

Abstract

Seizure unpredictability is rated as one of the most challenging aspects of living with epilepsy. Seizure likelihood can be influenced by a range of environmental and physiological factors that are difficult to measure and quantify. However, some generalizable patterns have been demonstrated in seizure onset. A majority of people with epilepsy exhibit circadian rhythms in their seizure times, and many also show slower, multiday patterns. Seizure cycles can be measured using a range of recording modalities, including self‐reported electronic seizure diaries. This study aimed to develop personalized forecasts from a mobile seizure diary app.

Authors

Philippa J. Karoly, Mark J. Cook, Matias Maturana, Ewan S. Nurse, Daniel Payne, Benjamin H. Brinkmann, David B. Grayden, Sonya B. Dumanis, Mark P. Richardson, Greg A. Worrell, Andreas Schulze‐Bonhage, Levin Kuhlmann and Dean R. Freestone

Published on 27 March 2020

Epilepsia

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Non-invasive measurements that influence seizure likelihood can be used to forecast risk.

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