Recent engineering and neuroscience applications have led to the development of brain–
computer interface (BCI) systems that improve the quality of life of people with motor …

This review article discusses the definition and implementation of brain–computer interface
(BCI) system relying on brain connectivity (BC) and machine learning/deep learning (DL) for …

Granger causality-based effective brain connectivity provides a powerful tool to probe the
neural mechanism for information processing and the potential features for brain computer …

Motor imagery (MI) is a brain-computer interface (BCI) technique in which specific brain
regions are activated when people imagine their limbs (or muscles) moving, even without …

Motor Imagery BCI systems have a high rate of users that are not capable of modulating their
brain activity accurately enough to communicate with the system. Several studies have …

Brain–computer interfaces (BCIs) make possible to interact with the external environment by
decoding the mental intention of individuals. BCIs can therefore be used to address basic …

Brain-computer interface (BCI) systems based on spontaneous electroencephalography
(EEG) hold the promise to implement human voluntary control of lower-extremity powered …

Brain-Computer Interfaces (BCIs) are systems that allow users to control devices using brain
activity alone. However, the ability of participants to command BCIs varies from subject to …

In this paper, we propose a novel EEG classification approach based on the Spatio-spectral
feature, aiming to design a motor movement/imagery classification model that extracts multi …

Stroke is a neurological condition that usually results in the loss of voluntary control of body
movements, making it difficult for individuals to perform activities of daily living (ADLs). Brain …