Objective. Electroencephalography (EEG) analysis has been an important tool in
neuroscience with applications in neuroscience, neural engineering (eg Brain–computer …

Epileptic seizure is one of the most chronic neurological diseases that instantaneously
disrupts the lifestyle of affected individuals. Toward develo** novel and efficient …

A variety of screening approaches have been proposed to diagnose epileptic seizures,
using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities …

In the previous decade, breakthroughs in the central nervous system bioinformatics and
computational innovation have prompted significant developments in brain–computer …

Background Epilepsy is one of the most common neurological conditions globally, and the
fourth most common in the United States. Recurrent non-provoked seizures characterize it …

Deep Learning (DL), a successful promising approach for discriminative and generative
tasks, has recently proved its high potential in 2D medical imaging analysis; however …

A central nervous system disorder is usually referred to as epilepsy. In epilepsy brain activity
becomes abnormal, leading to times of abnormal behavior or seizures, and at times loss of …

Correctly interpreting an Electroencephalography (EEG) signal with high accuracy is a
tedious and time-consuming task that may take several years of manual training due to its …

Harris Hawks Optimization (HHO) algorithm is a new metaheuristic algorithm, inspired by the
cooperative behavior and chasing style of Harris' Hawks in nature called surprise pounce …

Epileptic seizure detection using scalp electroencephalogram (sEEG) and intracranial
electroencephalogram (iEEG) has attracted widespread attention in recent two decades …