The benefits of early detection and classification of epileptic seizures in analysis, monitoring
and diagnosis for the realization and actualization of computer-aided devices and recent …

Abstract Brain-Computer Interfaces (BCI) is an exciting and emerging research area for
researchers and scientists. It is a suitable combination of software and hardware to operate …

Epilepsy is the only neurological condition for which electroencephalography (EEG) is the
primary diagnostic and important prognostic clinical tool. However, the manual inspection of …

In this paper, we propose and evaluate Epilepsy-Net, a collection of deep learning EEG
signal processing tools to detect epileptic seizures against non-epileptic seizures without …

Purpose Depression is a global challenge causing psychological and intellectual problems
that require efficient diagnosis. Electroencephalogram (EEG) signals represent the …

Despite promising advancements, closed-loop neurostimulation for drug-resistant epilepsy
(DRE) still relies on manual tuning and produces variable outcomes, while automated …

Epilepsy is a common neurological disorder that occurs at all ages. Epilepsy not only brings
physical pain to patients, but also brings a huge burden to the lives of patients and their …

Epilepsy is a brain disease in nerves which causes sudden seizure, sensations, and once in
a while loss of mindfulness. This disorder is difficult to find manually because of its …

One of the most critical processes is feature selection, which eliminates features that may
decrease classification performance and increase computational time. In this paper, we …

This paper presents a survey for optimization approaches that analyze and classify
electroencephalogram (EEG) signals. The automatic analysis of EEG presents a significant …