OBJECTIVE: To develop a prospective method for optimizing seizure prediction, given an
array of implanted electrodes and a set of candidate quantitative features computed at each …

Epileptic seizure prediction has steadily evolved from its conception in the 1970s, to proof-of-
principle experiments in the late 1980s and 1990s, to its current place as an area of …

Recent research has investigated the possibility of predicting epileptic seizures. Intervention
before the onset of seizure manifestations could be envisioned with accurate seizure …

Bivariate features, obtained from multichannel electroencephalogram recordings, quantify
the relation between different brain regions. Studies based on bivariate features have shown …

Combining multiple linear univariate features in one feature space and classifying the
feature space using machine learning methods could predict epileptic seizures in patients …

Research in seizure prediction has come a long way since its debut almost 4 decades ago.
Early studies suffered methodological caveats leading to overoptimistic results and lack of …

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 …

The prediction of epileptic seizures is crucial to aid patients in gaining early warning and
taking effective intervention. Several features have been explored to predict the onset via …

The First International Collaborative Workshop on Seizure Prediction was held at the
Department of Epileptology, University of Bonn, in Bonn, Germany on April 24–28, 2002 …

OBJECTIVE: In the present study, we have developed a novel patient-specific rule-based
seizure prediction system for focal neocortical epilepsy. METHODS: Five univariate …