The past decade has witnessed the rapid development of brain-computer interfaces (BCIs). contradiction between communication rates and tedious training processes become one major barriers restricting application steady-state visual-evoked potential (SSVEP)-based BCIs. A turbo detector was proposed in this study to resolve issue. uses filter bank canonical correlation analysis (FBCCA) as first-s...

The P300 is an endogenous event-related potential (ERP) that is naturally elicited by rare and significant external stimuli. P300s are used increasingly frequently in brain-computer interfaces (BCIs) because the users of ERP-based BCIs need no special training. However, P300 waves are hard to detect and, therefore, multiple target stimulus presentations are needed before an interface can make a...

Communication channel connecting the brain to a computer or other electronic devices is nothing but brain computer interface (BCI). The information extraction from brain is a very demanding task. Brain signals are mixed with other signals or noises coming from a finite set of brain activities that overlap in both time and space. Electroencephalogram (EEG) has been the most popular signal that i...

With a brain-computer interface (BCI), it is nowadays possible to achieve a direct pathway between the brain and computers thanks to the analysis of some particular brain activities. The detection of even-related potentials, like the P300 in the oddball paradigm exploited in P300-speller, provides a way to create BCIs by assigning several detected ERP to a command. Due to the noise present in t...

Electroencephalogram (EEG) based brain-computer interfaces (BCI) may provide a means of communication for those affected by severe paralysis. However, the relatively low information transfer rates (ITR) of these systems, currently limited to 1 bit/sec, present a serious obstacle to their widespread adoption in both clinical and non-clinical applications. Here, we report on the development of a ...