In a Mental Imagery Brain-Computer Interface the user has to perform specific mental task that generates electroencephalography (EEG) components, which can be translated in commands control BCI system. The development of high-performance MI-BCI requires long training, lasting several weeks or months, order improve ability manage his/her tasks. This works aims present design combining imaginary ...

Brain-computer interfaces (BCIs) are tools for controlling computers and other devices without using muscular activity, employing user-controlled variations in signals recorded from the user's brain. One of the most efficient noninvasive BCIs is based on the P300 wave of the brain's response to stimuli and is therefore referred to as the P300 BCI. Many modifications of this BCI have been propos...

The objective of this study was to investigate the efficacy of an Electroencephalography (EEG)-based Motor Imagery (MI) Brain-Computer Interface (BCI) coupled with a Haptic Knob (HK) robot for arm rehabilitation in stroke patients. In this three-arm, single-blind, randomized controlled trial; 21 chronic hemiplegic stroke patients (Fugl-Meyer Motor Assessment (FMMA) score 10-50), recruited after...

This paper investigates neurotechnologies for developing brain-computer interaction (BCI) based on the generative deep learning Stable Diffusion model. An algorithm modeling BCI is proposed and its training testing artificial data described. The results are encouraging researchers can be used in various areas of BCI, such as distance learning, remote medicine creation robotic humanoids, etc.

In this paper, for any non-empty subset C of a pseudo BCI-algebra X, the concept of p-closure of C, denoted by C(pc), is introduced and some related properties are investigated. Applying this concept, a characterization of the minimal elements of X is given. It is proved that C(pc) is the least closed pseudo BCI-ideal of X containing C and K(X) for any ideal C of X...

We first review the range of standalone and MATLAB-based software currently freely available to BCI researchers. We then discuss two MATLAB-centered solutions for realtime data streaming, the environments FieldTrip (Donders Institute, Nijmegen) and DataSuite (DataRiver, Producer, MatRiver) (Swartz Center, La Jolla). We illustrate the relative simplicity of coding BCI feature extraction and clas...

The project reported in this abstract aims to confirm whether a tactile stimulator ”touch– sense glove” is effective for a novel brain-computer interface (BCI) and whether it would improve BCI classification accuracies. We also report that tactile stimuli delivered to fingers could be utilized to evoke event related potential (ERP) responses with an attention modulation. The designed new stimul...

In this paper we identify developments that have led to the current interest from computer scientists in Brain-Computer Interfacing (BCI). Nondisabled users have become a target group for BCI applications. Non-disabled users can not be treated as patients. They are free to move and use their hands during the interaction with an application. Therefore BCI should be integrated in a multimodal app...

Brain-computer interfacing (BCI) is a steadily growing area of research. While initially BCI research was focused on applications for paralyzed patients, increasingly more alternative applications in healthy human subjects are proposed and investigated. In particular, monitoring of mental states and decoding of covert user states have seen a strong rise of interest. Here, we present some exampl...