EEG rhythm separation and time–frequency analysis of fast multivariate empirical mode decomposition for motor imagery BCI

Author:

Jiao Yang,Zheng Qian,Qiao Dan,Lang Xun,Xie Lei,Pan Yi

Funder

The Shenzhen Science and Technology Program

Publisher

Springer Science and Business Media LLC

Reference58 articles.

1. Altaheri H, Muhammad G, Alsulaiman M (2022) Physics-informed attention temporal convolutional network for EEG-based motor imagery classification. IEEE Trans Ind Inf 19(2):2249–58

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3. Ang KK, Chin ZY, Zhang H, Guan C (2008) Filter bank common spatial pattern (FBCSP) in brain-computer interface. In: 2008 IEEE international joint conference on neural networks (IEEE world congress on computational intelligence). IEEE, pp 2390–2397

4. Bashar SK, Bhuiyan MIH (2016) Classification of motor imagery movements using multivariate empirical mode decomposition and short time Fourier transform based hybrid method. Eng Sci Technol Int J 19(3):1457–64

5. Blankertz B, Dornhege G, Krauledat M, Müller KR, Curio G (2007) The non-invasive Berlin brain-computer interface: fast acquisition of effective performance in untrained subjects. Neuroimage 37(2):539–50

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