SAST-GCN: Segmentation Adaptive Spatial Temporal-Graph Convolutional Network for P3-Based Video Target Detection

SAST-GCN: Segmentation Adaptive Spatial Temporal-Graph Convolutional Network for P3-Based Video Target Detection

Detecting video-induced P3 is crucial to building the video target detection system based on the brain-computer interface. However, studies have shown that the brain response patterns corresponding to video-induced P3 are dynamic and determined by the interaction of multiple brain regions. This pape...

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Bibliographic Details
Main Authors: Runnan Lu, Ying Zeng, Rongkai Zhang, Bin Yan, Li Tong
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Neuroscience
Subjects:
brain-computer interface (BCI)
electroencephalography (EEG)
P3 detection
graph convolutional neural networks (GCN)
style-based recalibration module (SRM)
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2022.913027/full

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https://www.frontiersin.org/articles/10.3389/fnins.2022.913027/full

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