Ambulatory seizure forecasting with a wrist-worn device using long-short term memory deep learning

Abstract The ability to forecast seizures minutes to hours in advance of an event has been verified using invasive EEG devices, but has not been previously demonstrated using noninvasive wearable devices over long durations in an ambulatory setting. In this study we developed a seizure forecasting s...

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Bibliographic Details
Main Authors: Mona Nasseri, Tal Pal Attia, Boney Joseph, Nicholas M. Gregg, Ewan S. Nurse, Pedro F. Viana, Gregory Worrell, Matthias Dümpelmann, Mark P. Richardson, Dean R. Freestone, Benjamin H. Brinkmann
Format: article
Language:EN
Published: Nature Portfolio 2021
Subjects:
R
Q
Online Access:https://doaj.org/article/a602d4f7464843138012ca3c210ca25c
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