The P300 Speller has proven to be an effective paradigm for braincomputer interface (BCI) communication. Using this paradigm, studies have shown that a simple linear classifier can perform as well as more complex nonlinear classifiers. Several studies have examined methods such as Fisher’s Linear Discriminant (FLD), Stepwise Linear Discriminant Analysis (SWLDA), and Support Vector Machines (SVM...

The P300 speller is an example of a brain-computer interface that can restore functionality to victims of neuromuscular disorders. Although the most common application of this system has been communicating language, the properties and constraints of the linguistic domain have not to date been exploited when decoding brain signals that pertain to language. We hypothesized that combining the stan...

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...

A brain-computer interface (BCI) is a device that enables severely disabled people to communicate and interact with their environments using their brain waves. Most research investigating BCI in humans has used scalp-recorded electroencephalography or intracranial electrocorticography. The use of brain signals obtained directly from stereotactic depth electrodes to control a BCI has not previou...

Brain-Computer Interface (BCI) exploits the ability of human communication and control bypassing the classical neuromuscular communication channels. The BCI system described in this work is P300 speller. Two different paradigms of the P300 speller were proposed for higher accuracy: (i) the Single display (SD) paradigm that flashes each character individually in one stage and (ii) the Region-bas...

Motivated by P300 spelling scenarios involving communication based on a limited vocabulary, we propose a probabilistic graphical model-based framework and an associated classification algorithm that uses learned statistical prior models of language at the level of words. Exploiting such high-level contextual information helps reduce the error rate of the speller. The proposed approach models al...

Query spelling correction is a crucial component of moden search engines that can help users to express an information need more accurately and thus improve search quality. In participation of the Microsoft Speller Challenge, we proposed and implemented an efficient end-to-end speller correction system, namely CloudSpeller. The CloudSpeller system uses a Hidden Markov model to effectively model...

P300 is an electric signal emitted by brain about 300 milliseconds after a rare, but relevant-for-the-user event. Even if it is hard to identify and it provides a low-rate communication channel, it raises the interest of the scientific community because it can be used in cases in which other evoked potentials fail. One of the applications of this signal is a speller that enables subjects who lo...