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Motion-onset visual evoked potential (mVEP) has been recently proposed for EEG-based brain–computer interface (BCI) system. It is a scalp potential of visual motion response, and typically composed of three components: P1, N2, and P2. Usually several repetitions are needed to increase the signal-to-noise ratio (SNR) of mVEP, but more repetitions will cost more time thus lower the efficiency. Considering...
Brain-computer interface (BCI) systems enable humans to communicate with their environment by directly using brain signals. This way, body movement is not explicitly required for communication making this technology especially useful for people with limited mobility. In this study, the system performance and well-being of 38 subjects are investigated using two different layouts of graphical user interfaces...
Brain computer interface (BCI) is a methodology of utilizing the electrophysiological measures or the electroencephalographic (EEG) activity of the brain function in order to communicate with the exterior world through a non-muscular channel. It has become one of the primarily focussed fields of research that includes challenges for the various fields like Artificial intelligence, Cognitive neuroscience,...
A brain-computer interface (BCI) provides the possibility to translate brain neural activity patterns into control commands for computers without user's movement. The brain activity is most commonly measured non-invasively via standard electroencephalographic (EEG) electrodes placed on the surface of the scalp. We propose the evaluation of the Bremen-BCI system based on steady-state visual evoked...
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