… Seizure Cycles. This study sought to examine multiday cycles of heart rate and seizures in
… N=15) using wearable smartwatches and mobile seizure diaries over at least four months (M…

… Simply put, the likelihood of ictal involvement of any part of the CAN (and with it, the
probability of ictal chronotropic changes) increases with the volume of tissue in the …

… seizures from a smartphone app. The relationship between seizure onset time and phases
of seizure and heart rate … An additive regression model was used to project heart rate cycles. …

… For example, our recent work in seizure timing and heart rate, measured from a wearable
smartwatch, … The cyclical seizure likelihood is mostly attributable to multiday heart rate cycles. …

… Seizure Cycles. This study sought to examine multiday cycles of heart rate and seizures in
… N=15) using wearable smartwatches and mobile seizure diaries over at least four months (M…

… and analyzed EDA (sampling rate 4 Hz), peripheral body temperature (TEMP, sampling rate
4 Hz), and heart rate (HR, sampling rate 1 Hz). We calculated heart rate variability (HRV) by …

… Thus, for each new daily recording, we obtained a probability of belonging to the preictal
state, ie, the seizure likelihood. Accuracy of probabilistic predictions was estimated by the Brier …

… Heart rate 29, 30 and other physiological signals monitored from a smartwatch device 31 …
seizure likelihood. It is possible that these noncerebral biomarkers of seizure likelihood are …

… [9] RE Kleiger ea tl, Decreased heart rate variability and its association with increased …
Akaike, Information theory and an extension of the maximum likelihood principle, Proc. of the IEEE …

… This is an important limitation of our study as long-term factors, such as circadian or multidien
fluctuations in heart rate cycles are associated with seizure likelihood. However, we used …