Abstract Multichannel Electroencephalography-based Brain-Computer Interface (BCI)
systems facilitate a communicating medium between the human brain and the outside world …

Depression is a common cause of increased suicides worldwide, and studies have shown
that the number of patients suffering from major depressive disorder (MDD) increased …

Conventional passive lower limb rehabilitation is suboptimal since the brain is not actively
involved in the training. An autonomous motor imagery brain-computer interface (MI-BCI) …

Introduction Modern consciousness research has developed diagnostic tests to improve the
diagnostic accuracy of different states of consciousness via electroencephalography (EEG) …

Deep learning has achieved a remarkable success in areas such as brain-computer
interface systems (BCI). However, electroencephalography (EEG) signals evoked by motor …

In brain-computer interface (BCI) systems, challenges are presented by the recognition of
motor imagery (MI) brain signals. Established recognition approaches have achieved …

EEG signal analysis is difficult because there are so many unwanted impulses from non-
cerebral sources. Presently, methods for eliminating noise through selective frequency …

Background Brain-computer interface (BCI) systems based on motor imagery (MI) have
been widely used in neurorehabilitation. Feature extraction applied by the common spatial …

Purpose In order to improve the weak recognition accuracy and robustness of the
classification algorithm for brain-computer interface (BCI), this paper proposed a novel …

Background In post-stroke rehabilitation, functional connectivity (FC), motor-related cortical
potential (MRCP), and gait activities are common measures related to recovery outcomes …