Why the study?
Many EEG-based motor imagery studies for brain-computer interface systems do not make full use of brain network topology.
Does the M-GCN framework improve the decoding performance of EEG signals for motor imagery recognition in patients with spinal cord injury?
Does the M-GCN framework improve the decoding performance of EEG signals for motor imagery recognition in patients with spinal cord injury?
The proposed M-GCN framework achieves high accuracy in decoding EEG signals for motor imagery in spinal cord injury patients, potentially aiding in brain-computer interface-based rehabilitation.
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M-GCN may enhance EEG motor imagery decoding in spinal cord injury; leaves open prospective BCI validation before clinical use.
Xu et al. (2022) studied this question.
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