Phase-Locked Time-Shift Data Augmentation Method for SSVEP Brain-Computer Interfaces
Steady-state visual evoked potential (SSVEP) based brain-computer interfaces (BCIs) have achieved an information transfer rate (ITR) of over 300 bits/min, but abundant training data is required. The performance of SSVEP algorithms deteriorates greatly under limited data, and the existing time-shift...
Αποθηκεύτηκε σε:
| Κύριοι συγγραφείς: | , , , , |
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| Μορφή: | Artigo |
| Γλώσσα: | Inglês |
| Έκδοση: |
IEEE
2023-01-01
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| Σειρά: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| Θέματα: | |
| Διαθέσιμο Online: | https://ieeexplore.ieee.org/document/10275122/ |
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