Forecasting cycles of seizure likelihood

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..