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Cross-task cognitive workload recognition using a dynamic residual network with attention mechanism based on neurophysiological signals

https://doi.org/10.1016/j.cmpb.2023.107352

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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STEW: Simultaneous Task EEG Workload Data Set

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Spectral and Temporal Feature Learning With Two-Stream Neural Networks for Mental Workload Assessment

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Incoming claims: where this work appears in other papers’ reference lists and arguments.

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SCVCNet: Sliding Cross-Vector Convolution Network for Task-Independent Cognitive Workload Recognition With EEG Measurement

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Exploring Differential Entropy and Multifractal Cumulants for EEG-based Mental Workload Recognition

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Research on the classification of small civilian UAV operation competency level based on EEG and BCAM-LSTM network

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Task-Independent Cognitive Workload Discrimination Based on EEG with Stacked Graph Attention Convolutional Networks

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Human-Centric Cognitive State Recognition Using Physiological Signals: A Systematic Review of Machine Learning Strategies Across Application Domains

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