Three-stage transfer learning for motor imagery EEG recognition
Author:
Funder
Natural Science Foundation of Zhejiang Province
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11517-024-03036-9.pdf
Reference44 articles.
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3. Foong R, Ang KK, Quek C, Guan C, Phua KS, Kuah CWK, Deshmukh VA, Yam LHL, Rajeswaran DK, Tang N, Chew E, Chua KSG (2020) Assessment of the efficacy of EEG-based MI-BCI with visual feedback and EEG correlates of mental fatigue for upper-limb stroke rehabilitation. IEEE Trans Biomed Eng 67(3):786–795. https://doi.org/10.1109/TBME.2019.2921198
4. Khan MA, Saibene M, Das R, Brunner I, Puthusserypady S (2012) Emergence of flexible technology in developing advanced systems for post-stroke rehabilitation: a comprehensive review. J Neural Eng 18(6):061003. https://doi.org/10.1088/1741-2552/ac36aa
5. Lee J, Lee D, Jeong I, Cho. J (2021) A Study on the content of mental and physical stability game in virtual reality through EEG detection. In: 2021 International Conference on Information and Communication Technology Convergence (ICTC), Jeju Island, Korea, pp 693–696. https://doi.org/10.1109/ICTC52510.2021.9620932
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