BACKGROUND Brain-Computer Interface (BCI) is a set of technologies that are of increasing interest to researchers. BCI has been proposed as assistive technology for individuals who are non-communicative or paralyzed, such as those with amyotrophic lateral sclerosis or spinal cord injury. The technology has also been suggested for enhancement and entertainment uses, and there are companies curre...

Electroencephalogram (EEG) based Brain Computer Interface (BCI) is a system that uses human brainwaves recorded from the scalp as a means for providing a new communication channel by which people with limited physical communication capability can effect control over devices such as moving a mouse and typing characters. Evolutionary approaches have the potential to improve the performance of suc...

A brain-computer interface (BCI) is a hardware and software communications system that permits cerebral activity alone to control computers or external devices. The immediate goal of BCI research is to provide communications capabilities to severely disabled people who are totally paralyzed or 'locked in' by neurological neuromuscular disorders, such as amyotrophic lateral sclerosis, brain stem...

Automatic systems capable of understanding different facets of human communication will be at the heart of human-computer interfaces (HCI) in the near future. An HCI which is built on the guiding principle: "think and make it happen without any physical effort" is called a brain-computer interface (BCI). Indeed, the "think" part of this principle involves the human brain, "make it happen" impli...

Operating brain-actuated devices requires split attention between the interaction of the device with its environment and the Brain-Computer Interface (BCI) feedback. In case of screen-based applications it is possible to merge BCI feedback and application, but not in case of controlling devices, like wheelchairs or exoskeletons. Recently we demonstrated that BCI feedback could be provided via t...

We have integrated the Graz brain-computer interface (BCI) system with a highly-immersive virtual reality (VR) Cave-like system. This setting allows for a new type of experience, whereby participants can control a virtual world using imagination of movement. However, current BCI systems still have many limitations. In this paper we present two experiments exploring the different constraints pos...

In the brain-computer interface based on P300 wave (P300 BCI), selection of command by user becomes possible due to focusing user's attention external stimulus/command and extraction response this stimulus in form event-related potential (ERP) components from EEG. To obtain ERP signal, stimuli should be repeated many times, however, view existing variability latency certain stimuli, averaged ER...

The aim of this study was to compare methods for feature extraction and classification of EEG signals for a brain–computer interface (BCI) according to different mental task conditions. EEG data was obtained either from BCI data base or from EEG experimental recording. There were different methods for feature Extraction like temporal methods, frequential methods, and Time-frequency representati...

Abstract In this review article, we present more than a decade of our work on the development brain–computer interface (BCI) systems for restoration walking following neurological injuries such as spinal cord injury (SCI) or stroke. Most has been in domain non-invasive electroencephalogram-based BCIs, including interfacing system with virtual reality environment and physical prostheses. Real-ti...

Recent research suggests the brain can learn almost any brain-computer interface (BCI) configuration; however, contrasting behavioral evidence from structural learning theory argues that previous experience facilitates, or impedes, future learning. A study by Sadtler and colleagues (Nature 512: 423-426, 2014) used BCI to demonstrate that neural network structural characteristics constrain learn...