Abstract Drug-resistant, multifocal, non-resectable epilepsies are among the most difficult
epileptic disorders to manage. An approach to control previously uncontrollable seizures in …

Patients´ views on the relevance, performance requirements, and implementation of seizure
prediction devices have so far not been evaluated in a standardized form. We here report …

Background The interplay between sleep structure and seizure probability has previously
been studied using electroencephalography (EEG). Combining sleep assessment and …

Epilepsy is one of the most prevalent neurological diseases among humans and can lead to
severe brain injuries, strokes, and brain tumors. Early detection of seizures can help to …

Objective: The objective of this work is the development of an accurate seizure forecasting
algorithm that considers brain's functional connectivity for electrode selection. Methods: We …

Over the last decade, the search for a method able to reliably predict seizures hours in
advance has been largely replaced by the more realistic goal of very early detection of …

Background Many electroencephalography (EEG) based seizure detection paradigms have
been developed and validated over the last two decades. The majority of clinical …

Although there are numerous studies exploring basic neuronal mechanisms that are likely to
be associated with seizures, to date no definite information is available as to how, when, or …

Objective Prediction of epileptic seizures can improve the living conditions for refractory
epilepsy patients. We aimed to improve sensitivity and specificity of prediction methods, and …

Background Epilepsy is the 4th most common neurological disorder and is characterized by
recurrent, unpredictable seizures. The ability to forecast seizures is a significant unmet need …