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Found 3 papers, 2 papers with code
GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery Signals
To conclude, the GCNs-Net filters EEG signals based on the functional topological relationship, which manages to decode relevant features for brain motor imagery.
Attention-based Graph ResNet for Motor Intent Detection from Raw EEG signals
In previous studies, decoding electroencephalography (EEG) signals has not considered the topological relationship of EEG electrodes.
Deep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition
The introduced deep feature mining approach can precisely recognize human motion intents from raw EEG signals, which paves the road to translate the EEG based MI recognition to practical BCI systems.
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