A crossover-graph convolution network based on spatio-temporal filter for EEG motion intention decoding

doi:10.1016/j.bspc.2026.109578

A crossover-graph convolution network based on spatio-temporal filter for EEG motion intention decoding

2026-01-14

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DOI：10.1016/j.bspc.2026.109578

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• Construct electrode connectivity relationships based on frequency-domain Granger causality. • Spatio-temporal filtering enhances EEG resolution by removing redundancy. • Feature-crossover GCN fuses multi-scale features dynamically. • Online BCI system validates efficient motor intention decoding.

A crossover-graph convolution network based on spatio-temporal filter for EEG motion intention decoding

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