Similar to functional magnetic resonance imaging (fMRI), functional near-infrared
spectroscopy (fNIRS) detects the changes of hemoglobin species inside the brain, but via …

Sleep specialists often conduct manual sleep stage scoring by visually inspecting the
patient's neurophysiological signals collected at sleep labs. This is, generally, a very difficult …

This report is the second part of a comprehensive two-part series aimed at reviewing an
extensive and diverse toolkit of novel methods to explore brain health and function. While …

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 article, non-invasive hybrid brain–computer interface (hBCI) technologies for
improving classification accuracy and increasing the number of commands are reviewed …

In this paper, a hybrid electroencephalography–functional near-infrared spectroscopy (EEG–
fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain …

This research presents a brain-computer interface (BCI) framework for brain signal
classification using deep learning (DL) and machine learning (ML) approaches on functional …

There is growing interest for implementing tools to monitor cognitive performance in
naturalistic work and everyday life settings. The emerging field of research, known as …

In recent years, major depressive disorder (MDD) has been shown to negatively impact
physical recovery in a variety of patients. Functional near-infrared spectroscopy (fNIRS) is a …

In this study, we determine the optimal feature-combination for classification of functional
near-infrared spectroscopy (fNIRS) signals with the best accuracies for development of a two …