Motor Imagery Decoding in the Presence of Distraction Using Graph Sequence Neural Networks
In this study, we propose a graph sequence neural network (GSNN) to accurately decode patterns of motor imagery from electroencephalograms (EEGs) in the presence of distractions. GSNN aims to build subgraphs by exploiting biological topologies among brain regions to capture local and global relation...
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| Main Authors: | , , , , |
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| Format: | Book |
| Published: |
IEEE,
2022-01-01T00:00:00Z.
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| Subjects: | |
| Online Access: | Connect to this object online. |
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