Purpose The purpose of this review paper is to address the substantial challenges of the
outdated exoskeletons used for rehabilitation and further study the current advancements in …

Neurological disease victims may be completely paralyzed and unable to move, but they
may still be able to think. Their brain activity is the only means by which they can interact …

Since the nonlinear and non-stationary characteristics of electroencephalogram (EEG)
signals, motor imagery based brain-computer interface (MI-BCI) have problems of poor …

Brain signal patterns generated in the central nervous system of brain-computer interface
(BCI) users are closely related to BCI paradigms and neural coding. In BCI systems, BCI …

Studying the motor-control mechanisms of the brain is critical in academia and also has
practical implications because techniques such as brain-computer interfaces (BCIs) can be …

Objective. Visual evoked potentials (VEPs) have been commonly applied in brain-computer
interfaces (BCIs) due to their satisfactory classification performance recently. However, most …

Accurate quantification of cortical engagement during mental imagery tasks remains a
challenging brain‐imaging problem with immediate relevance to developing brain …

Objective: Most Deep Learning (DL) methods for the classification of functional Near-Infrared
Spectroscopy (fNIRS) signals do so without explaining which features contribute to the …

Mind-uploading, the vision of transferring human consciousness into a digital realm, relies
on a profound comprehension of the brain and cutting-edge technology. Non-invasive …

Magnetoencephalography (MEG) records the extremely weak magnetic fields on the surface
of the scalp through highly sensitive sensors. Multi-channel MEG data provide higher spatial …