In a recent study by Sellers et al. (1) a patient in locked-in state after brainstem stroke was able to successfully communicate via electroencephalography (EEG) based brain computer interface (BCI) employing a P300 speller paradigm. BCI uses the brain signal, which can either be the electrical signal (electroencephalography-EEG) (2) or a change in hemodynamic activity [functional magnetic reso...

Current research in brain computer interface (BCI) technology is advancing beyond preclinical studies, with trials beginning in human patients. To date, these trials have been carried out with several different types of recording interfaces. The success of these devices has varied widely, but different factors such as the level of invasiveness, timescale of recorded information, and ability to ...

effects of hall current, ion-slip and coriolis force on unsteady mhd couette-hartmann flow of a viscous incompressible electrically conducting fluid through a porous medium bounded by porous plates in the presence of a uniform transverse magnetic field which is either fixed relative to the fluid or to the moving porous plate is investigated using laplace transform technique. the expressions for...

OBJECTIVE The P300 speller is a common brain-computer interface (BCI) application designed to communicate language by detecting event related potentials in a subject's electroencephalogram signal. Information about the structure of natural language can be valuable for BCI communication, but attempts to use this information have thus far been limited to rudimentary n-gram models. While more soph...

Restorative brain-computer interfaces (BCI) are increasingly used to provide feedback of neuronal states in a bid to normalize pathological brain activity and achieve behavioral gains. However, patients and healthy subjects alike often show a large variability, or even inability, of brain self-regulation for BCI control, known as BCI illiteracy. Although current co-adaptive algorithms are power...

Current non-invasive brain-computer interfaces such as those based on electroencephalography (EEG) [1] suffer from the problem of low signal-to-noise ratio, making fine-grained moment-by-moment control tedious and exhausting for users. To address this problem, we have previously proposed an adaptive hierarchical approach to brain-computer interfacing: users teach the BCI system new skills on-th...

In this paper, we study soft rough BCI-algebras with respect to MSapproximation spaces. Some new soft rough operations over BCI-algebras are explored. In particular, lower and upper soft rough BCI-algebras with another soft set are investigated. Finally, a kind of decision making method for soft rough BCI-algebras are originally investigated.

In this position paper we describe part of the Dutch BrainGain research project on Brain Computer Interfacing (BCI) and our planned research in this project. We focus on BCI research for healthy users. In the BrainGain project our task is to look at Human Factors aspects of BCI applications, to look at multimodal interactions that include BCI interactions, and to design games, game environments...

Brain-Computer Interface (BCI) is a way to control computers by using human brain waves. As the technology has improved, BCI devices have become smaller and cheaper, making it possible for more individuals to buy them. This allows BCI to be applied to new fields outside of pure research, including entertainment. We examine whether BCI devices can be used as a new gaming device, approaching it f...