Comparison of subject-independent and subject-specific EEG-based BCI using LDA and SVM classifiers
Author:
Funder
FAPESP
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Biomedical Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11517-023-02769-3.pdf
Reference27 articles.
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2. Mcfarland DJ, Wolpaw JR (2005) Sensorimotor rhythm-based brain – computer regression improves performance. Neural Syst. Rehabil. Eng. IEEE Trans. 13(3):372–379. https://doi.org/10.1109/TNSRE.2005.848627
3. Jackson PL, Lafleur MF, Malouin F, Richards C, Doyon J (2001) Potential role of mental practice using motor imagery in neurologic rehabilitation. Arch. Phys. Med. Rehabil. 82(8):1133–1141. https://doi.org/10.1053/apmr.2001.24286
4. C. Neuper and G. Pfurtscheller, “Neurofeedback training for BCI control.” Springer, pp. 65–78, 2010.
5. B. Z. Allison and C. Neuper, “Could anyone use a BCI?” Springer Verlag, pp. 35–54, 2010.
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