Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those
using motor-imagery (MI) data, have the potential to become groundbreaking technologies …

Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as
state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis …

A brain-computer interface (BCI) is a communication system that allows the use of brain
activity to control computers or other external devices. It can, by bypassing the peripheral …

Since the discovery of the EEG principles by Berger in the 20's, procedures for artifact
removal have been essential in its pre-processing. In literature, diverse approaches based …

In this study, a brain-computer interface (BCI) framework for hybrid functional near-infrared
spectroscopy (fNIRS) and electroencephalography (EEG) for locked-in syndrome (LIS) …

In this paper, hybrid brain-computer interface (hBCI) technologies for improving
classification accuracy and increasing the number of commands are reviewed. Hybridization …

Background Common spatial pattern (CSP) has been most popularly applied to motor-
imagery (MI) feature extraction for classification in brain–computer interface (BCI) …

Investigations of the neuro-physiological correlates of mental loads, or states, have attracted
significant attention recently, as it is particularly important to evaluate mental fatigue in …

Abstract Functional Near-Infrared Spectroscopy (fNIRS) maps human brain function by
measuring and imaging local changes in hemoglobin concentrations in the brain that arise …

In the last decade, virtual reality (VR) training has been used extensively in video games
and military training to provide a sense of realism and environmental interaction to its users …