ISSN Print 2500–1094
ISSN Online 2542–1204
Bulletin of RSMU
BIOMEDICAL JOURNAL OF PIROGOV UNIVERSITY (MOSCOW, RUSSIA)
ORIGINAL RESEARCH
High-speed brain-computer communication interface based on code-modulated visual evoked potentials
About authors
1 Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
2 Department of Mechanics and Mathematics, Lomonosov Moscow State University, Moscow, Russia
Correspondence should be addressed: Rafael K. Grigoryan
Leninskie Gory 1, bld. 12, Moscow, 119234; moc.liamg@oib.hparrg
About paper
Author contribution: Grigoryan RK — experiment planning and conducting, data processing, article authoring; Filatov DB — experiment planning, software development, article authoring; Kaplan AY — task setting, experiment planning, general research effort management, article authoring.
Received: 2018-07-29
Accepted: 2019-03-24
Published online: 2019-04-05
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Fig. 1. Neurointerface utilization by users: indicators. 1 — command input accuracy; 2 — average command input time (in seconds); 3 — information transfer rate, bpm; A — basis stimulus sequence; B — inverted; C — slow mode; D — fast mode
Fig. 2. Averaged evoked potentials registered during stimulation, all channels, shifted to zero shift relative to the basis m-sequence. The stimulus sequence is given in gray. One curve — one channel of the averaged EEG. The potential averaged between all channels is given in black
Fig. 3. Correlation function's maximum value maps, averaged for all participants, for averaged evoked potential of each channel (Fig. 2) and individual evoked potentials
for single m-sequences. This indicator allows assessing the intensity of potential in all channels
