A substantial number of patients who survive severe brain injury progress to a nonresponsive state of wakeful unawareness, referred to as a vegetative state (VS). They appear to be awake, but show no signs of awareness of themselves, or of their environment in repeated clinical examinations. However, recent neuroimaging research demonstrates that some VS patients can respond to commands by will...

A substantial number of patients who survive severe brain injury progress to a nonresponsive state of wakeful unawareness, referred to as a vegetative state (VS). They appear to be awake, but show no signs of awareness of themselves, or of their environment in repeated clinical examinations. However, recent neuroimaging research demonstrates that some VS patients can respond to commands by will...

Developments in neuroscience, signal processing and machine learning are enabling device control using our brain activity. Specifically, current technology allows us to record braingenerated signals in real time, infer the human intention and translate it into control commands for external devices. These brain-computer interfaces (BCIs) can currently control virtual keyboards, games, smart whee...

BACKGROUND Brain computer interfaces (BCI) based on electro-encephalography (EEG) have been shown to detect mental states accurately and non-invasively, but the equipment required so far is cumbersome and the resulting signal is difficult to analyze. BCI requires accurate classification of small amplitude brain signal components in single trials from recordings which can be compromised by curre...

A Brain Computer Interface (BCI) system takes and classifies a user’s brain activity into a signal to which a computer can respond. To control a BCI, the user should produce various brain activity patterns which are captured in form of Electroencephalogram (EEG) and converted to commands by identifying the patterns by the system. Such classification was undertaken by various methods, and perfor...

Brain-computer interfaces (BCIs) aim to provide a mechanism by which individuals with severe forms of paralysis can communicate their wishes to others or gain control over devices in their environment. This paper describes the evaluation of an interface designed for use with BCI, which is dedicated to providing a flexible and extensible framework for controlling multiple devices within a domest...

Brain computer interfaces allow users to preform various tasks using only the electrical activity of the brain. BCI applications often present the user a set of stimuli and record the corresponding electrical response. The BCI algorithm will then have to decode the acquired brain response and perform the desired task. In rapid serial visual presentation (RSVP) tasks, the subject is presented wi...

Mental-Imagery based Brain-Computer Interfaces (MI-BCIs) allow their users to send commands to a computer using their brain-activity alone (typically measured by ElectroEncephaloGraphy-EEG), which is processed while they perform specific mental tasks. While very promising, MI-BCIs remain barely used outside laboratories because of the difficulty encountered by users to control them. Indeed, alt...

Brain-computer interfaces represent a range of acknowledged technologies that translate brain activity into computer commands. The aim of our research is to develop and evaluate a BCI control application for certain assistive technologies that can be used for remote telepresence or remote driving. The communication channel to the target device is based on the steady-state visual evoked potentia...

Brain-computer interfaces (BCI) allow users to “communicate” with a computer without using their muscles. BCI based on sensori-motor rhythms use imaginary motor tasks, such as moving the right or left hand, to send control signals. The performances of a BCI can vary greatly across users but also depend on the tasks used, making the problem of appropriate task selection an important issue. This ...