DMG-GCN: A Dynamic Microstate-Guided Graph Convolutional Network for EEG Cognitive Workload Decoding in Air Traffic Control.

Zhang Y, Shao Q, Yang H, Ren X, Peng X

DOI: 10.3390/bios16080452
Published: 2026 Aug 20
Container: Biosensors
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/bios16080452,
  title = {DMG-GCN: A Dynamic Microstate-Guided Graph Convolutional Network for EEG Cognitive Workload Decoding in Air Traffic Control.},
  author = {Zhang Y and Shao Q and Yang H and Ren X and Peng X},
  year = {2026},
  journal = {Biosensors},
  doi = {10.3390/bios16080452},
  url = {https://doi.org/10.3390/bios16080452}
}

RIS

TY  - JOUR
TI  - DMG-GCN: A Dynamic Microstate-Guided Graph Convolutional Network for EEG Cognitive Workload Decoding in Air Traffic Control.
AU  - Zhang Y
AU  - Shao Q
AU  - Yang H
AU  - Ren X
AU  - Peng X
PY  - 2026
JO  - Biosensors
DO  - 10.3390/bios16080452
UR  - https://doi.org/10.3390/bios16080452
ER  -

APA

Y, Z., Q, S., H, Y., X, R., & X, P. (2026). DMG-GCN: A Dynamic Microstate-Guided Graph Convolutional Network for EEG Cognitive Workload Decoding in Air Traffic Control.. Biosensors. https://doi.org/10.3390/bios16080452

Source records

pubmed · retrieved 2026-09-25T07:55:18.362Z