A significant proportion of the electroencephalography (EEG) literature focuses on
differences in historically pre-defined frequency bands in the power spectrum that are …

There has been an increasing trend towards the use of complexity analysis in quantifying
neural activity measured by electroencephalography (EEG) signals. On top of revealing …

Abstract In 1999, the International Federation of Clinical Neurophysiology (IFCN) published
“IFCN Guidelines for topographic and frequency analysis of EEGs and EPs”(Nuwer et al …

Objective: Many EEG studies have reported that ADHD is characterized by elevated
Theta/Beta ratio (TBR). In this study we conducted a meta-analysis on the TBR in ADHD …

The convolutional neural network (CNN) is a mainstream deep learning (DL) algorithm.
However, the application of DL techniques in attention-deficit/hyperactivity disorder (ADHD) …

Neurofeedback (NFB) is emerging as a promising technique that enables self-regulation of
ongoing brain oscillations. However, despite a rise in empirical evidence attesting to its …

Rapid progress in information and communication technologies (ICTs) has fueled the
popularity of e‐learning. However, an e‐learning environment is limited in that online …

Background Attention deficit hyperactivity disorder (ADHD) is a ubiquitous
neurodevelopmental disorder affecting many children. Therefore, automated diagnosis of …

This article reviews the eyes-open and eyes-closed resting electroencephalogram (EEG)
literature for Attention-Deficit/Hyperactivity Disorder (AD/HD) from 2002 to 2019. This time …

The electroencephalogram (EEG) is an informative neuroimaging tool for studying attention-
deficit/hyperactivity disorder (ADHD); one main goal is to characterize the EEG of children …