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We report the design and performance of a brain-computer interface (BCI) system for real-time single-trial binary classification of viewed images based on participant-specific dynamic brain response signatures in high-density (128-channel) electroencephalographic (EEG) data acquired during a rapid serial visual presentation (RSVP) task. Image clips were(More)
The purpose of this paper is to evaluate whether mu rhythm based BCIs can be implemented using the low cost Emotiv Epoc EEG device. Synchronisation in the high alpha and low beta band caused by continuous imagery and real toes movement was recorded on 6 healthy subjects. We apply LDA and SVM classifiers in order to classify a trial as movement or(More)
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