Recruiting neural field theory for data augmentation in a motor imagery brain-computer interface
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We introduce a novel approach to training data augmentation in brain-computer interfaces (BCIs) using neural field theory (NFT) applied to EEG data from motor imagery tasks. BCIs often suffer from limited accuracy due to a limited amount of training data. To a... ...
