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...

The wavelength dependency of transparent current is investigated theoretically and empirically for bulk and quantum-well (QW) materials. A new analytical formula is presented for obtaining accurate Fermi levels of QW structures under current injection. The transparent current can be described with an exponential function of the wavelength using two fitting parameters. The simple expression can ...

brain-computer interfaces (bci) record brain signals, analyze and translate them into control commands which are relayed to output devices that carry out desired actions. these systems do not use normal neuromuscular output pathways. actually, the principal goal of bci systems is to provide better life style for physically-challenged people which are suffered from cerebral palsy, amyotrophic la...

Brain-computer interface (BCI) research deals with establishing communication pathways between the brain and external devices. BCI systems can be broadly classified depending on the placement of the electrodes used to detect and measure neurons firing in the brain: in invasive systems, electrodes are inserted directly into the cortex; in noninvasive systems, they are placed on the scalp and use...

The field of brainYcomputer interface (BCI) research began to develop about 25 years ago and transformed from initially isolated demonstrations by a few groups into a large scientific enterprise that is currently producing hundreds of peer-reviewed articles and several dedicated conferences and workshops each year. This level of productivity is reflective of the large and continually growing en...

Motor imagery–based brain–computer interface (BCI) using electroencephalography (EEG) has demonstrated promising applications by directly decoding users’ movement related mental intention. The selection of control signals, e.g., the channel configuration and decoding algorithm, plays a vital role in the online performance and progressing of BCI control. While several offline analyses report the...

In this paper we introduce the concept of Brain-Computer Interface (BCI) inhibitor, which is meant to standby the BCI until the user is ready, in order to improve the overall performance and usability of the system. BCI inhibitor can be defined as a system that monitors user’s state and inhibits BCI interaction until specific requirements (e.g. brain activity pattern, user attention level) are ...

Brain-computer interfaces (BCIs) translate brain activity into signals controlling external devices. BCIs based on visual stimuli can maintain communication in severely paralyzed patients, but only if intact vision is available. Debilitating neurological disorders however, may lead to loss of intact vision. The current study explores the feasibility of an auditory BCI. Sixteen healthy volunteer...