AIBullisharXiv – CS AI · 6h ago6/10
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EVA-Net: Subject-Independent EEG Motor Decoding with Video-Derived Motor Priors
Researchers propose EVA-Net, a machine learning framework that uses video-based motor priors to improve EEG brain-computer interfaces (BCIs) across different subjects with minimal calibration. The two-stage approach achieves 8.66% accuracy improvement over existing methods, demonstrating that video is a more effective semantic anchor than text for decoding motor intent from brain signals.