nASR is an end-to-end trainable Keras layer for channel-level EEG artifact subspace reconstruction that outperforms traditional ASR with 6-8x faster inference on BCI Competition IV data.
A robust adaptive denoising framework for real-time artifact removal in scalp EEG measurements,
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nASR: An End-to-End Trainable Neural Layer for Channel-Level EEG Artifact Subspace Reconstruction in Real-Time BCI
nASR is an end-to-end trainable Keras layer for channel-level EEG artifact subspace reconstruction that outperforms traditional ASR with 6-8x faster inference on BCI Competition IV data.