Translational gaps and opportunities for medical wearables in digital health
A confluence of advances in biosensor technologies, enhancements in health care delivery
mechanisms, and improvements in machine learning, together with an increased awareness …
mechanisms, and improvements in machine learning, together with an increased awareness …
Wearable digital health technology for epilepsy
E Donner, O Devinsky, D Friedman - New England Journal of …, 2024 - Mass Medical Soc
Wearable Digital Health Technology for Epilepsy | New England Journal of Medicine Skip to main
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Seizure occurrence is linked to multiday cycles in diverse physiological signals
Objective The factors that influence seizure timing are poorly understood, and seizure
unpredictability remains a major cause of disability. Work in chronobiology has shown that …
unpredictability remains a major cause of disability. Work in chronobiology has shown that …
Seizure forecasting: bifurcations in the long and winding road
To date, the unpredictability of seizures remains a source of suffering for people with
epilepsy, motivating decades of research into methods to forecast seizures. Originally, only …
epilepsy, motivating decades of research into methods to forecast seizures. Originally, only …
Machine learning and artificial intelligence applications to epilepsy: a review for the practicing epileptologist
WT Kerr, KN McFarlane - Current Neurology and Neuroscience Reports, 2023 - Springer
Abstract Purpose of Review Machine Learning (ML) and Artificial Intelligence (AI) are data-
driven techniques to translate raw data into applicable and interpretable insights that can …
driven techniques to translate raw data into applicable and interpretable insights that can …
Seizure detection and prediction by parallel memristive convolutional neural networks
During the past two decades, epileptic seizure detection and prediction algorithms have
evolved rapidly. However, despite significant performance improvements, their hardware …
evolved rapidly. However, despite significant performance improvements, their hardware …
Artificial intelligence‐enhanced epileptic seizure detection by wearables
Objective Wrist‐or ankle‐worn devices are less intrusive than the widely used
electroencephalographic (EEG) systems for monitoring epileptic seizures. Using custom …
electroencephalographic (EEG) systems for monitoring epileptic seizures. Using custom …
Seizure forecasting using minimally invasive, ultra‐long‐term subcutaneous electroencephalography: individualized intrapatient models
Objective One of the most disabling aspects of living with chronic epilepsy is the
unpredictability of seizures. Cumulative research in the past decades has advanced our …
unpredictability of seizures. Cumulative research in the past decades has advanced our …
The evolution of antiseizure medication therapy selection in adults: Is artificial intelligence-assisted antiseizure medication selection ready for prime time?
CL Gunasekera, JI Sirven… - Journal of Central …, 2023 - journals.sagepub.com
Antiseizure medications (ASMs) are the mainstay of symptomatic epilepsy treatment. The
primary goal of pharmacotherapy with ASMs in epilepsy is to achieve complete seizure …
primary goal of pharmacotherapy with ASMs in epilepsy is to achieve complete seizure …
Seizure forecasting using minimally invasive, ultra‐long‐term subcutaneous EEG: generalizable cross‐patient models
This study describes a generalized cross‐patient seizure‐forecasting approach using
recurrent neural networks with ultra‐long‐term subcutaneous EEG (sqEEG) recordings …
recurrent neural networks with ultra‐long‐term subcutaneous EEG (sqEEG) recordings …