A Two-Stream Graph Convolutional Network Based on Brain Connectivity for Anesthetized States Analysis

IEEE Transactions on Neural Systems and Rehabilitation Engineering, Год журнала: 2022, Номер 30, С. 2077 - 2087

Опубликована: Янв. 1, 2022

Investigating neural mechanisms of anesthesia process and developing efficient anesthetized state detection methods are especially on high demand for clinical consciousness monitoring. Traditional monitoring not involved with the topological changes between electrodes covering prefrontal-parietal cortices, by investigating electrocorticography (ECoG). To fill this gap, a framework based two-stream graph convolutional network (GCN) was proposed, i.e., one stream extracting structure features, other node features. The includes GCN Model 1 2. For 1, brain connectivity networks were constructed using phase lag index (PLI), representing different A common adjacency matrix founded through dual-graph method, features expressed nodes. Therefore, traditional spectral can be directly applied graphs changing structures. On hand, average absolute signal amplitudes calculated as then fully connected these input This method learns both nodes graph, uses approach to enhance focus Based ECoG signals monkeys, results show that which distinguish awake state, moderate sedation deep achieved an accuracy 92.75% in group-level experiments mean 93.50% subject-level experiments. Our work verifies excellence monitoring, recognition also shows may carry neurological markers associated anesthesia.

Язык: Английский

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Generating ten BCI commands using four simple motor imageries and classification by divergence-based DNN

Neural Computing and Applications, Год журнала: 2022, Номер 35(2), С. 1303 - 1322

Опубликована: Сен. 26, 2022

Язык: Английский

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Wading corvus optimization based text generation using deep CNN and BiLSTM classifiers

Biomedical Signal Processing and Control, Год журнала: 2022, Номер 78, С. 103969 - 103969

Опубликована: Авг. 5, 2022

Язык: Английский

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Msrtnet: Multi-Scale Spatial Residual Network Based on Time-Domain Transformer

Опубликована: Янв. 1, 2024

Язык: Английский

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EEG Signal Based Human Emotion Recognition Brain-computer Interface using Deep Learning and High-Performance Computing

Wireless Personal Communications, Год журнала: 2024, Номер unknown

Опубликована: Дек. 23, 2024

Язык: Английский

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