A sequential learning model with GNN for EEG-EMG-based stroke rehabilitation BCI

A sequential learning model with GNN for EEG-EMG-based stroke rehabilitation BCI

IntroductionBrain-computer interfaces (BCIs) have the potential in providing neurofeedback for stroke patients to improve motor rehabilitation. However, current BCIs often only detect general motor intentions and lack the precise information needed for complex movement execution, mainly due to insuf...

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Bibliographic Details
Main Authors: Haoyang Li, Hongfei Ji, Jian Yu, Jie Li, Lingjing Jin, Lingyu Liu, Zhongfei Bai, Chen Ye
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-04-01
Series:Frontiers in Neuroscience
Subjects:
brain-computer interfaces
neurofeedback
graph neural network
stroke rehabilitation
corticomuscular coherence
sequential learning
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2023.1125230/full

Internet

https://www.frontiersin.org/articles/10.3389/fnins.2023.1125230/full

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