Brain source localization has been consistently implemented over the recent years to
elucidate complex brain operations, pairing the high temporal resolution of the EEG with the …

In this article, we provide an overview of electroencephalography (EEG) source imaging
(ESI) of movement decoding for brain-computer interface (BCI) applications. The current …

Objective. In electroencephalography (EEG)-based brain–computer interface (BCI) systems
for motor control tasks the conventional practice is to decode motor intentions by using scalp …

EEG-based brain–computer interfaces (BCI) have promising therapeutic potential beyond
traditional neurofeedback training, such as enabling personalized and optimized virtual …

This paper describes the implementation of a Brain Computer Interface (BCI) scheme using
a common spatial patterns (CSP) filter in combination with a Recursive Least Squares (RLS) …

Objective. The brain-computer interface (BCI) system based on sensorimotor rhythm can
convert the human spirit into instructions for machine control, and it is a new human …

Studying the decoding process of complex grasping movement is of great significance to the
field of motor rehabilitation. This study aims to decode five natural reach-and-grasp types …

Brain–computer interfaces based on electroencephalography (EEG) often exhibit unreliable
performance in the classification of motor tasks. Recent research has shown that EEG …

In the BCI rehabilitation system, the decoding of motor imagery tasks (MI-tasks) with dipoles
in the source domain has gradually become a new research focus. For complex multiclass …

Objective. The common spatial patterns (CSP) algorithm is an effective method to extract
discriminatory features from electroencephalography (EEG) to be used by a brain–computer …