Although notable progress has been made in the study of Steady-State Visual Evoked
Potential (SSVEP)-based Brain-Computer Interface (BCI), several factors that limit the …

The application study of robot control based brain-computer interface (BCI) not only helps to
promote the practicality of BCI but also helps to promote the advancement of robot …

Objective. Brain–computer interface (BCI) system has developed rapidly in the past decade.
And rapid serial visual presentation (RSVP) is an important BCI paradigm to detect the …

Substantial developments have been established in the past few years for enhancing the
performance of brain–computer interface (BCI) based on steady-state visual evoked …

The optimization of coding stimulus is a crucial factor in the study of steady-state visual
evoked potential (SSVEP)-based brain-computer interface (BCI). This study proposed an …

To address the issues of low control accuracy, insufficient command quantity, and limited
machine functionality in brain-machine interfaces (BMIs), we propose a multifunctional robot …

In general, a large amount of training data can effectively improve the classification
performance of the Steady-State Visually Evoked Potential (SSVEP)-based Brain-Computer …

Objective. Brain–computer interface (BCI) systemsdirectly translate human intentions to
instructions for machines by decoding the neural signals. The rapid serial visual …

Objective Frequency recognition methods based on spatial filtering have been widely
studied to enhance the classification performance of steady-state visual evoked potential …

This paper reports on a benchmark dataset acquired with a brain–computer interface (BCI)
system based on the rapid serial visual presentation (RSVP) paradigm. The dataset consists …