Brainloop
 
4. BCI - Brain–computer interfaces 
  4.2. Present-day BCIs
  4.2.1. Visual evoked potentials

In the 1970s, Jacques Vidal developed a system that satisfied the current definition of a dependent BCI (Vidal, 1973, 1977).

This system used the VEP recorded from the scalp over visual cortex to determine the direction of eye gaze, and thus to determine the direction in which the user wished to move a cursor.

Brain response interface (BRI) uses the VEPs produced by brief visual stimuli and recorded from the scalp over visual cortex. The user faces a video screen displaying 64 symbols (e.g. letters) in an 8 x 8 grid and looks at the symbol he or she wants to select. Subgroups of these 64 symbols undergo an equiluminant red/green alternation or a fine red/green check pattern alternation 40–70 times/s. Each symbol is included in several subgroups, and the entire set of subgroups is presented several times. Each subgroup’s VEP amplitude about 100 ms after the stimulus is computed and compared to a VEP template already established for the user. From these comparisons, the system determines with high accuracy the symbol that the user is looking at. A keyboard interface gives access to output devices. Normal volunteers can use it to operate a word processing program at 10–12 words/min.

Middendorf (2000) reported another method for using VEPs to determine gaze direction.

Several virtual buttons appear on a screen and flash at different rates. The user looks at a button and the system determines the frequency of the photic driving response over visual cortex. When this frequency matches that of a button, the system concludes that the user wants to select it. These VEP-based communication systems depend on the user’s ability to control gaze direction.


 
4. BCI - Intro
  4.1. Definition and features of a BCI
  4.1.1. Dependent and independent BCIs
4.1.2. BCI use is a skill
4.1.3. The parts of a BCI
  4.1.3.1. Signal acquisition
4.1.3.2. Signal processing: feature extraction
4.1.3.3. Signal processing: the translation algorithm
4.1.3.4. The output device
4.1.3.5. The operating protocol
4.2. Present-day BCIs
  4.2.1. Visual evoked potentials
4.2.2. Slow cortical potentials
4.2.3. P300 evoked potentials
4.2.4. Mu and beta rhythms
  4.2.4.1. The Wadsworth BCI
4.2.4.2. The Graz BCI
4.2.5. Cortical neuronal action potentials
4.3. The future of BCI-based communication
   

Source: Brain–computer interfaces for communication and control, Clinical Neurophysiology 113 (2002) 767–791, Jonathan R. Wolpaw, Niels Birbaumer, Dennis J. McFarland, Gert Pfurtscheller, Theresa M. Vaughan
 
 
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