A standard four-layer MLP trained end-to-end on raw EEG+fNIRS+MoCap data reports at least 90% test accuracy for five-class activity recognition on ten subjects.
Validating deep neural networks for online decoding of motor imagery movements from eeg signals
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An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing
A standard four-layer MLP trained end-to-end on raw EEG+fNIRS+MoCap data reports at least 90% test accuracy for five-class activity recognition on ten subjects.