Current rehabilitation therapies for stroke rely on physical practice (PP) by the patients.
Motor imagery (MI), the imagination of movements without physical action, presents an …

Multi-channel EEG data are usually necessary for spatial pattern identification in motor
imagery (MI)-based brain computer interfaces (BCIs). To some extent, signals from some …

Lack of adequate training samples and noisy high-dimensional features are key challenges
faced by Motor Imagery (MI) decoding algorithms for electroencephalogram (EEG) based …

Common spatial pattern (CSP)-based spatial filtering has been most popularly applied to
electroencephalogram (EEG) feature extraction for motor imagery (MI) classification in brain …

Drowsiness is characterized by reduced attentiveness, commonly experienced during the
transition from wakefulness to sleepiness. It can decrease an individual's alertness, thereby …

Electroencephalography (EEG)–based motor imagery (MI) brain-computer interface (BCI)
technology has the potential to restore motor function by inducing activity-dependent brain …

Convolutional neural networks (CNNs) have recently been applied to electroencephalogram
(EEG)-based brain–computer interfaces (BCIs). EEG is a noninvasive neuroimaging …

Electroencephalograph (EEG), the representation of the brain's electrical activity, is a widely
used measure of brain activities such as working memory during cognitive tasks. Varying in …

Motor imagery (MI) brain–computer interface (BCI) and neurofeedback (NF) with
electroencephalogram (EEG) signals are commonly used for motor function improvement in …

Decoding of motor imagery (MI) from Electroencephalogram (EEG) is an important
component of BCI system that helps motor-disabled people interact with the outside world …