Recent review papers have investigated seizure prediction, creating the possibility of
preempting epileptic seizures. Correct seizure prediction can significantly improve the …

Epilepsy, a neurological disorder in which patients suffer from recurring seizures, affects
approximately 1% of the world population. In spite of available drug and surgical treatment …

This paper presents a signal modeling-based new methodology of automatic seizure
detection in EEG signals. The proposed method consists of three stages. First, a multirate …

Epileptic seizures are known for their unpredictable nature. However, recent research
provides that the transition to seizure event is not random but the result of evidence …

Several electroencephalogram (EEG)-based predictive models for automated epilepsy
diagnosis have been proposed over more than a decade. However, to the best of our …

Typical seizure prediction models aim at discriminating interictal brain activity from pre-
seizure electrographic patterns. Given the lack of a preictal clinical definition, a fixed interval …

OBJECTIVE: Retrospective evaluation and comparison of performances of a multivariate
method for seizure detection and prediction on simultaneous long-term EEG recordings from …

The dramatic success of pacemakers, cardiac defibrillators, cochlear implants and now brain
stimulation for movement disorders has kindled enormous interest in translating …

The unpredictability of epileptic seizures is one of the most problematic aspects of the field of
epilepsy. Methods or devices capable of detecting seizures minutes before they occur may …

Epilepsy, a neurological disorder in which patients suffer from recurring seizures, affects
approximately 1% of the world population. In spite of available drug and surgical treatment …