abstract brian computer interface (bci) is a direct communication pathway between the brain and an external device. bcis are often aimed at assisting, augmenting or repairing human cognitive or sensory-motor functions. in this work a new algorithm is introduced to enhancing eeg signals that have been concerned the p300 problem. signal to noise ratio of eeg signals is very low and have  much art...

OBJECTIVE The P300 speller is a brain-computer interface (BCI) that can possibly restore communication abilities to individuals with severe neuromuscular disabilities, such as amyotrophic lateral sclerosis (ALS), by exploiting elicited brain signals in electroencephalography (EEG) data. However, accurate spelling with BCIs is slow due to the need to average data over multiple trials to increase...

We present an auditory stimulus optimization and a pilot study of a two–step input speller application combined with a spatial auditory brain–computer interface (saBCI) for paralyzed users. The application has been developed for 45, out of 48 defining the full set, Japanese kana characters in a two–step input procedure setting for an easy–to–use BCI–speller interface. The user first selects the...

Many brain–computer interface (BCI) studies overlook the channel optimization due to its inherent complexity. However, a careful selection increases performance and users’ comfort while reducing cost of system. Evolutionary meta-heuristics, which have demonstrated their usefulness in solving complex problems, not been fully exploited yet this context. The purpose study is two-fold: (1) propose ...

More and more effort is done in BCI research to improve its usability for patients, with respect to its communication speed and transmission accuracy. In this contribution, we experiment with BCI speller based on P300 evoked potential. More precisely, the typical form of event-related potential (ERP) inspires us to devise classification methods based on the similarity/dissimilarity in the time ...