Journal article

Forecasting cycles of seizure likelihood

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, Dean R Freestone

Epilepsia | Wiley | Published : 2020

Abstract

Objective 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. Methods Forecasts based on circadian and m..

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Grants

Awarded by National Health and Medical Research Council


Funding Acknowledgements

National Health and Medical Research Council, Grant/Award Number: APP 1130468 and APP 1178220; Epilepsy Foundation