Development of EEG-based brain computer interface (BCI) methods has largely focused on creating a communication channel for subjects with intact cognition but profound loss of motor control from stroke or neurodegenerative disease, allowing such subjects to communicate by spelling out words on a personal computer. However, another important human communication channel may also be limited or una...

A large number of incommensurable metrics are currently used to report the performance of brain-computer interfaces (BCI) used for augmentative and alterative communication (AAC). The lack of standard metrics precludes the comparison of different BCI-based AAC systems, hindering rapid growth and development of this technology. This paper presents a review of the metrics that have been used to r...

In recent years, research on Brain-Computer Interface (BCI) technology for healthy users has attracted considerable interest, and BCI games are especially popular. This study reviews the current status of, and describes future directions, in the field of BCI games. To this end, we conducted a literature search and found that BCI control paradigms using electroencephalographic signals (motor ima...

Our objective was to develop and validate a new brain-computer interface (BCI) system suitable for long-term independent home use by people with severe motor disabilities. The BCI was used by a 51-year-old male with ALS who could no longer use conventional assistive devices. Caregivers learned to place the electrode cap, add electrode gel, and turn on the BCI. After calibration, the system allo...

OBJECTIVE While promising, electroencephaloraphy based brain-computer interfaces (BCIs) are barely used due to their lack of reliability: 15% to 30% of users are unable to control a BCI. Standard training protocols may be partly responsible as they do not satisfy recommendations from psychology. Our main objective was to determine in practice to what extent standard training protocols impact us...

‎let $s$ be a subset of a finite group $g$‎. ‎the bi-cayley graph ${rm bcay}(g,s)$ of $g$ with respect to $s$ is an undirected graph with vertex set $gtimes{1,2}$ and edge set ${{(x,1),(sx,2)}mid xin g‎, ‎ sin s}$‎. ‎a bi-cayley graph ${rm bcay}(g,s)$ is called a bci-graph if for any bi-cayley graph ${rm bcay}(g,t)$‎, ‎whenever ${rm bcay}(g,s)cong {rm bcay}(g,t)$ we have $t=gs^alpha$ for some $...

Development of EEG-based brain computer interface (BCI) methods has largely focused on creating a communication channel for subjects with intact cognition but profound loss of motor control from stroke or neurodegenerative disease that allows such subjects to communicate by spelling out words on a personal computer. However, other important human communication channels may also be limited or un...

A Brain-Computer Interface (BCI) allows a user to control a computer by pure brain activity. Due to the nonstationarity of the recorded brain signals, the BCI performance tends to decrease over time. Recently, adaption of the BCI has been proposed as a means to counter non-stationarity and help to stabilize the BCI performance. Since most adaption methods for BCI are analysed in an offline sett...

It is widely accepted in the brain computer interface (BCI) research community that neurological phenomena are the only source of control in any BCI system. Artifacts are undesirable signals that can interfere with neurological phenomena. They may change the characteristics of neurological phenomena or even be mistakenly used as the source of control in BCI systems. Electrooculography (EOG) and...

In this thesis, the usage of fuzzy classification algorithms in brain-computer interfaces (BCI) based on electroencephalography (EEG) is researched. We review the existing literature on BCI, the traditional crisp algorithms often used in BCI for classification, fuzzy classification algorithms and their application in BCI. A simple BCI system is implemented that allows the user to move a cursor ...