FAAR is a new automated artifact rejection method using compact features and adaptive Signal Quality Index thresholds that improves MI-BCI performance most in low-baseline conditions and reduces inter-subject variability across 13 public datasets.
Improved Riemannian potato field: An automatic artifact rejection method for EEG
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From EEG Cleaning to Decoding: The Role of Artifact Rejection in MI-based BCIs
FAAR is a new automated artifact rejection method using compact features and adaptive Signal Quality Index thresholds that improves MI-BCI performance most in low-baseline conditions and reduces inter-subject variability across 13 public datasets.