A single lightweight CNN classifies EEG from three BCI paradigms with 88.39% accuracy on OpenBMI, beating EEGNet, DeepConvNet, EEG-Inception, and EEGITNet.
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Cross-BCI, A Cross-BCI-Paradigm Classifica-tion Model Towards Universal BCI Applications
A single lightweight CNN classifies EEG from three BCI paradigms with 88.39% accuracy on OpenBMI, beating EEGNet, DeepConvNet, EEG-Inception, and EEGITNet.