Natural image reconstruction from brain waves: a novel visual BCI system with native feedback
Grigory Rashkov, Anatoly S. BobeiD, Dmitry Fastovets, Maria V. Komarova
Abstract
Here we hypothesize that observing the visual stimuli of different categories trigger distinct brain states that can be decoded from noninvasive EEG recordings. We introduce an effective closed-loop BCI system that reconstructs the observed or imagined stimuli images from the co-occurring brain wave parameters. The reconstructed images are presented to the subject as a visual feedback. The developed system is applicable to training BCI-naive subjects because of the user-friendly and intuitive way the visual patterns are employed to modify the brain states.
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