End-to-end P300 BCI using Bayesian accumulation of Riemannian probabilities. (arXiv:2203.07807v2 [cs.LG] UPDATED)

In brain-computer interfaces (BCI), most of the approaches based on
event-related potential (ERP) focus on the detection of P300, aiming for single
trial classification for a speller task. While this is an important objective,
existing P300 BCI still require several repetitions to achieve a correct
classification accuracy. Signal processing and machine learning advances in
P300 BCI mostly revolve around the P300 detection part, leaving the character
classification out of the scope. To reduce the number of repetitions while
maintaining a …

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