March 26, 2024, 4:42 a.m. | Ivo Pascal de Jong, L\"uke Luna van den Wittenboer, Matias Valdenegro-Toro, Andreea Ioana Sburlea

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.15431v1 Announce Type: cross
Abstract: Public Motor Imagery-based brain-computer interface (BCI) datasets are being used to develop increasingly good classifiers. However, they usually follow discrete paradigms where participants perform Motor Imagery at regularly timed intervals. It is often unclear what changes may happen in the EEG patterns when users attempt to perform a control task with such a BCI. This may lead to generalisation errors. We demonstrate a new paradigm containing a standard calibration session and a novel BCI control …

abstract arxiv bci brain brain-computer interface classifiers computer control cs.hc cs.lg datasets eeg eess.sp features good however patterns public type

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