Improving Motor Imagery-Based Brain-Computer Interfaces with Chebyshev Graph Neural Networks
Author:
Affiliation:
1. School of Physics and Electronics, Shandong Normal University,Jinan,Shandong
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10334522/10334524/10334539.pdf?arnumber=10334539
Reference12 articles.
1. Breaking the silence: Brain?computer interfaces (BCI) for communication and motor control
2. Electroencephalographic Motor Imagery Brain Connectivity Analysis for BCI: A Review
3. Deep CNN model based on serial-parallel structure optimization for four-class motor imagery EEG classification
4. A Model Combining Multi Branch Spectral-Temporal CNN, Efficient Channel Attention, and LightGBM for MI-BCI Classification
5. Study of MI-BCI classification method based on the Riemannian transform of personalized EEG spatiotemporal features
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