We investigate various forms of face-to-face and multiparty interac‐ tions in the context of potential brain-computer interface interactions (BCI). BCI has been employed in clinical applications but more recently also in domestic and game and entertainment applications. This paper focusses on multi-party game applications. That is, BCI game applications that allow multiple users and different B...

The brain computer interface (BCI) should be the accessibility solution “par excellence” for interactive and e-learning systems. There is a substantial tradition of research on the human electro encephalogram (EEG) and on BCI systems that are based, inter alia, on EEG measurement. We have not yet seen a viable BCI for e-learning. For many users for a BCI based interface is their first choice fo...

A new parallel man-machine training approach to brain-computer interface (BCI) succeeded through a unique application of machine learning methods. The BCI system could train users to control an animated cursor on the computer screen by voluntary electroencephalogram (EEG) modulation. Our BCI system requires only two to four electrodes, and has a relatively short training time for both the user ...

Brain-computer interface (BCI) is a communication system that translates brain activity into commands for a computer or other digital device. The majority of BCI systems work by reading and interpreting cortically-evoked electro-potentials (“brain waves”) via an electroencephalogram (EEG) data. The EEG data is inherently complex. The signals are non-linear, non-stationary and therefore difficul...

This review discusses machine learning methods and their application to Brain-Computer Interfacing. A particular focus is placed on feature selection. We also point out common flaws when validating machine learning methods in the context of BCI. Finally we provide a brief overview on the Berlin-Brain Computer Interface (BBCI).

The number of people with disabilities is increasing, so it requires bionic devices to replace human motor functions. Brain-Computer Interface (BCI) can be a tool for the device communicate brain. Signal brain or Electroencephalogram (EEG) signal need classify drive corresponding device. This research goal imagination right and left-hand movements based on EEG signal. system design in this cons...

A Brain Computer Interface (BCI) is a communication system that receives neurological signals from the brain and translates them into control commands for electrical (e.g., computer mouse) and electromechanical (e.g., Wheelchair) devices. The development of such systems was intended originally to aid individuals with a condition called locked-in syndrome. Individuals with this condition have lo...

The study of Human–Computer Interfaces (HCI) provides a challenge for future interaction research and development. Brain-Computer Interfaces (BCI) is a part or a subset of Human-Computer Interaction (HCI) that involves the communication between the user and the system via brain signals. The electroencephalography (EEG) have developed into one of the most important and widely used quantitative d...

A brain-Computer interface (BCI), also known as brain-machine interface (BMI), utilizes neurophysiological correlates of voluntary cognitive tasks to facilitate direct communication between human brain and computing devices without the involvement of neuro-muscular pathways. This emerging research area has the potential to contribute significantly to enhancing the accessibility of ICT systems f...

Brain-computer interface (BCI) systems based on the steady-state visual evoked potential (SSVEP) provide higher information throughput and require shorter training than BCI systems using other brain signals. To elicit an SSVEP, a repetitive visual stimulus (RVS) has to be presented to the user. The RVS can be rendered on a computer screen by alternating graphical patterns, or with external ligh...