A brain-computer interface (BCI) provides the possibility to translate brain neural activity patterns into control commands without movement by the user. In recent years, there has been increasing interest in using steady-state visual evoked potential (SSVEP) in BCI systems; the SSVEP approach provides currently the fastest and most reliable communication paradigm for the implementation of a no...

A promising approach for brain-computer interfaces (BCIs) employs the steady-state visual evoked potential (SSVEP) for extracting control information. Main advantages of these SSVEP BCIs are a simple and low-cost setup, little effort to adjust the system parameters to the user and comparatively high information transfer rates (ITR). However, traditional frequency-coded SSVEP BCIs require the us...

OBJECTIVES We study the applicability of a visual P3-based and a Steady State Visually Evoked Potentials (SSVEP)-based Brain-Computer Interfaces (BCIs) for mental text spelling on a cohort of patients with incomplete Locked-In Syndrome (LIS). METHODS Seven patients performed repeated sessions with each BCI. We assessed BCI performance, mental workload and overall satisfaction for both systems...

Although the feasibility of brain-computer interface (BCI) systems based on steady-state visual evoked potential (SSVEP) has been extensively investigated, only a few studies have evaluated its clinical feasibility in patients with locked-in syndrome (LIS), who are the main targets of BCI technology. The main objective of this case report was to share our experiences of SSVEP-based BCI experime...

The feature extraction of Steady-State Visual Evoked Potential (SSVEP) is developed in a frequency domain regardless of the limitation in hardware architecture. We introduced a spectrum intensity ratio as a simple characterization and separation of SSVEP. However, it is difficult to classify an unseeing state of subjects. In this paper, we propose an adaptive threshold to reject the unseeing st...

Brain-computer interfaces (BCIs), independent of the brain's normal output pathways, are attracting an increasing amount of attention as devices that extract neural information. As a typical type of BCI system, the steady-state visual evoked potential (SSVEP)-based BCIs possess a high signal-to-noise ratio and information transfer rate. However, the current high speed SSVEP-BCIs were implemente...

This article concerns one of the most important problems of brain-computer interfaces (BCI) based on Steady State Visual Evoked Potentials (SSVEP), that is the selection of the a-priori most suitable frequencies for stimulation. Previous works related to this problem were done either with measuring systems that have little in common with actual BCI systems (e.g., single flashing LED) or were pr...

BACKGROUND Brain computer interface (BCI) is an emerging technology for paralyzed patients to communicate with external environments. Among current BCIs, the steady-state visual evoked potential (SSVEP)-based BCI has drawn great attention due to its characteristics of easy preparation, high information transfer rate (ITR), high accuracy, and low cost. However, electroencephalogram (EEG) signals...

Endogenous attention modulates the amplitude and phase coherence of steady-state visual-evoked potentials (SSVEPs). In efforts to decipher the neural mechanisms of attentional modulation, we compared the time course of attentional modulation of SSVEP amplitude (thought to reflect the magnitude of neural population activity) and phase coherence (thought to reflect neural response synchronization...