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 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 …

Objective Tracking seizures is crucial for epilepsy monitoring and treatment evaluation.
Current epilepsy care relies on caretaker seizure diaries, but clinical seizure monitoring may …

Objective New devices are needed for monitoring seizures, especially those associated with
sudden unexpected death in epilepsy (SUDEP). They must be unobtrusive and automated …

Objective To explore the feasibility of home monitoring of epilepsy patients with a novel
subcutaneous electroencephalography (EEG) device, including clinical implications, safety …

Persons who suffer from intractable seizures are safer if attended when seizures strike.
Consequently, there is a need for wearable devices capable of detecting both convulsive …

Data mining is an important research activity in the field of medical sciences since there is a
requirement of efficient methodologies for analyzing and detecting diseases. Data mining …

Epileptic seizures have a great impact on the quality of life of people who suffer from them
and further limit their independence. For this reason, a device that would be able to monitor …

One-fourths of the patients have medication-resistant seizures and require seizure detection
and treatment continuously to cope with sudden seizures. Seizures can be detected by …

Objective Wrist‐or ankle‐worn devices are less intrusive than the widely used
electroencephalographic (EEG) systems for monitoring epileptic seizures. Using custom …