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Objective
Wrist‐ or ankle‐worn devices are less intrusive than the widely used electroencephalographic (EEG) systems for monitoring epileptic seizures. Using custom‐developed deep‐learning seizure detection models, we demonstrate the detection of a broad range of seizure types by wearable signals.
Methods
Patients admitted to the epilepsy monitoring unit were enrolled and asked to wear wearable...
Objective
Tracking seizures is crucial for epilepsy monitoring and treatment evaluation. Current epilepsy care relies on caretaker seizure diaries, but clinical seizure monitoring may miss seizures. Wearable devices may be better tolerated and more suitable for long‐term ambulatory monitoring. This study evaluates the seizure detection performance of custom‐developed machine learning (ML) algorithms...
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