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Published in IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2020
A motor imagery-based BCI using zero-shot learning reduces calibration time and achieves 91.81% of traditional method accuracy.
Recommended citation: Duan, L., Li, J., Ji, H., Pang, Z., Zheng, X., Lu, R., ... & Zhuang, J. (2020). Zero-shot learning for EEG classification in motor imagery-based BCI system. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(11), 2411-2419. https://doi.org/10.1109/TNSRE.2020.3027004
Published in Computational and Mathematical Methods in Medicine, 2020
The motor-imagery brain-computer interface (MI-BCI) system improves by using command combinations and transfer learning to reduce calibration time and increase accuracy.
Recommended citation: Zheng, X., Li, J., Ji, H., Duan, L., Li, M., Pang, Z., ... & Tianhao, G. (2020). Task Transfer Learning for EEG Classification in Motor Imagery‐Based BCI System. Computational and Mathematical Methods in Medicine, 2020(1), 6056383. https://doi.org/10.1155/2020/6056383
Published in Pain (unpublished), 2024
The study found that short-term variability in chronic musculoskeletal pain is stable, clinically relevant, and may inform personalized pain management.
Recommended citation: unpublished unpublished
Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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