Accurate identification of seizure activity, both clinical and subclinical, has important
implications in the management of epilepsy. Accurate recognition of seizure activity is …

Inaccurate subjective seizure counting poses treatment and diagnostic challenges and thus
suboptimal quality in epilepsy management. The limitations of existing hospital‐and home …

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 …

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 …

Abstract The Epilepsy Innovation Institute (Ei2) is a new research program of the Epilepsy
Foundation designed to be an innovation incubator for epilepsy. Ei2 research areas are …

Seizure forecasting has the potential to create new therapeutic strategies for epilepsy, such
as providing patient warnings and delivering preemptive therapy. Progress on seizure …

This study describes a generalized cross‐patient seizure‐forecasting approach using
recurrent neural networks with ultra‐long‐term subcutaneous EEG (sqEEG) recordings …

Objective. This paper introduces a fully automated, subject-specific deep-learning
convolutional neural network (CNN) system for forecasting seizures using ambulatory …

Background Seizure detection is challenging outside the clinical environment due to the lack
of comfortable, reliable, and practical long-term neurophysiological monitoring devices. We …

Epilepsy is the second most common neurological disorder, affecting 0.6–0.8% of the
world's population. In this neurological disorder, abnormal activity of the brain causes …