Cycles in epilepsy
Epilepsy is among the most dynamic disorders in neurology. A canonical view holds that
seizures, the characteristic sign of epilepsy, occur at random, but, for centuries, humans …
seizures, the characteristic sign of epilepsy, occur at random, but, for centuries, humans …
Machine learning for predicting epileptic seizures using EEG signals: A review
With the advancement in artificial intelligence (AI) and machine learning (ML) techniques,
researchers are striving towards employing these techniques for advancing clinical practice …
researchers are striving towards employing these techniques for advancing clinical practice …
Forecasting seizure risk in adults with focal epilepsy: a development and validation study
Background People with epilepsy are burdened with the apparent unpredictability of
seizures. In the past decade, converging evidence from studies using chronic EEG (cEEG) …
seizures. In the past decade, converging evidence from studies using chronic EEG (cEEG) …
Seizure cycles in focal epilepsy
Importance Focal epilepsy is characterized by the cyclical recurrence of seizures, but, to our
knowledge, the prevalence and patterns of seizure cycles are unknown. Objective To …
knowledge, the prevalence and patterns of seizure cycles are unknown. Objective To …
[HTML][HTML] Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic
It is a major challenge in clinical epilepsy to diagnose and treat a disease characterized by
infrequent seizures based on patient or caregiver reports and limited duration clinical …
infrequent seizures based on patient or caregiver reports and limited duration clinical …
Machine learning and wearable devices of the future
Abstract Machine learning (ML) is increasingly recognized as a useful tool in healthcare
applications, including epilepsy. One of the most important applications of ML in epilepsy is …
applications, including epilepsy. One of the most important applications of ML in epilepsy is …
[HTML][HTML] Ambulatory seizure forecasting with a wrist-worn device using long-short term memory deep learning
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 …
using invasive EEG devices, but has not been previously demonstrated using noninvasive …
Seizure forecasting and cyclic control of seizures
Epilepsy is a unique neurologic condition characterized by recurrent seizures, where
causes, underlying biomarkers, triggers, and patterns differ across individuals. The …
causes, underlying biomarkers, triggers, and patterns differ across individuals. The …
Research on acoustic emission multi-parameter characteristics in the failure process of imitation steel fiber reinforced concrete
H Li, X Li, J Fu, Z Gao, P Chen, Z Zhang - Physics of Fluids, 2023 - pubs.aip.org
Studies of the damage process of fiber-reinforced concrete through acoustic emission are
very significant for concrete structural health monitoring. In this study, three specifications of …
very significant for concrete structural health monitoring. In this study, three specifications of …
[HTML][HTML] Seizure forecasting using a novel sub-scalp ultra-long term EEG monitoring system
Accurate identification of seizure activity, both clinical and subclinical, has important
implications in the management of epilepsy. Accurate recognition of seizure activity is …
implications in the management of epilepsy. Accurate recognition of seizure activity is …