A brain-computer interface (BCI) affords real-time communication, significantly improving the
quality of lifecycle, brain-to-internet (B2I) connectivity, and communication between the brain …

A brain–computer interface (BCI) can connect humans and machines directly and has
achieved successful applications in the past few decades. Many new BCI paradigms and …

It has been almost 50 years since the term ''brain–computer interface”(BCI) was first
proposed by Jacques J. Vidal in 1973 [1]. Unlike traditional electronic interfaces that transmit …

Objective. Steady-state visual evoked potential (SSVEP) is an essential paradigm of
electroencephalogram based brain–computer interface (BCI). Previous studies in the BCI …

Objective. Brain-controlled robotic arms have shown broad application prospects with the
development of robotics, science and information decoding. However, disadvantages, such …

BCI systems use motor imagery to allow users to control external devices through their brain
activity. They extract neural signals from the brain using a large number of EEG channels …

Background and objective The use of adaptive signal decomposition methods and machine
learning (ML) algorithms have gained interest in biomedical applications. Brain-computer …

Currently, most of the high-performance models for frequency recognition of steady-state
visual evoked potentials (SSVEPs) are linear. However, SSVEPs collected from different …

An essential priority of visual brain-computer interfaces (BCIs) is to enhance the information
transfer rate (ITR) to achieve high-speed communication. Despite notable progress …

The practical functionality of a brain-computer interface (BCI) is critically affected by the
number of stimuli, especially for steady-state visual evoked potential based BCI (SSVEP …