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Cross-task-oriented EEG signal analysis methods: Our opinion.

作者信息

Wen Dong, Pang Zhenhua, Wan Xianglong, Li Jingjing, Dong Xianling, Zhou Yanhong

机构信息

School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China.

Key Laboratory of Perception and Control of Intelligent Bionic Unmanned Systems, Ministry of Education, Institute of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China.

出版信息

Front Neurosci. 2023 Mar 9;17:1153060. doi: 10.3389/fnins.2023.1153060. eCollection 2023.

DOI:10.3389/fnins.2023.1153060
PMID:36968485
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10033669/
Abstract
摘要

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EEG Based Dynamic Functional Connectivity Analysis in Mental Workload Tasks With Different Types of Information.基于脑电图的不同类型信息下脑力工作负荷任务的动态功能连接分析。
IEEE Trans Neural Syst Rehabil Eng. 2022;30:632-642. doi: 10.1109/TNSRE.2022.3156546. Epub 2022 Mar 21.
2
Cross-Task Cognitive Workload Recognition Based on EEG and Domain Adaptation.基于 EEG 和领域自适应的跨任务认知工作负荷识别。
IEEE Trans Neural Syst Rehabil Eng. 2022;30:50-60. doi: 10.1109/TNSRE.2022.3140456. Epub 2022 Jan 28.
3
Cross-Task Consistency of Electroencephalography-Based Mental Workload Indicators: Comparisons Between Power Spectral Density and Task-Irrelevant Auditory Event-Related Potentials.基于脑电图的心理负荷指标的跨任务一致性：功率谱密度与任务无关听觉事件相关电位的比较
Front Neurosci. 2021 Nov 16;15:703139. doi: 10.3389/fnins.2021.703139. eCollection 2021.
4
Label-Based Alignment Multi-Source Domain Adaptation for Cross-Subject EEG Fatigue Mental State Evaluation.基于标签对齐的多源域自适应用于跨个体脑电图疲劳精神状态评估
Front Hum Neurosci. 2021 Oct 1;15:706270. doi: 10.3389/fnhum.2021.706270. eCollection 2021.
5
Generalized Deep Learning EEG Models for Cross-Participant and Cross-Task Detection of the Vigilance Decrement in Sustained Attention Tasks.基于广义深度学习的脑电模型在持续性注意任务警觉下降的跨被试和跨任务检测。
Sensors (Basel). 2021 Aug 20;21(16):5617. doi: 10.3390/s21165617.
6
A deep descriptor for cross-tasking EEG-based recognition.一种用于基于脑电图的跨任务识别的深度描述符。
PeerJ Comput Sci. 2021 May 19;7:e549. doi: 10.7717/peerj-cs.549. eCollection 2021.
7
EEG Fingerprints of Task-Independent Mental Workload Discrimination.基于脑电图的任务无关脑力负荷识别特征。
IEEE J Biomed Health Inform. 2021 Oct;25(10):3824-3833. doi: 10.1109/JBHI.2021.3085131. Epub 2021 Oct 5.
8
Continuous decoding of cognitive load from electroencephalography reveals task-general and task-specific correlates.从脑电图中持续解码认知负荷揭示了任务通用和任务特定的相关性。
J Neural Eng. 2020 Oct 16;17(5):056016. doi: 10.1088/1741-2552/abb9bc.
9
Learning Spatial-Spectral-Temporal EEG Features With Recurrent 3D Convolutional Neural Networks for Cross-Task Mental Workload Assessment.基于循环三维卷积神经网络学习空间-谱-时 EEG 特征进行跨任务精神工作负荷评估。
IEEE Trans Neural Syst Rehabil Eng. 2019 Jan;27(1):31-42. doi: 10.1109/TNSRE.2018.2884641. Epub 2018 Dec 3.
10
An Evaluation of EEG-based Metrics for Engagement Assessment of Distance Learners.基于脑电图的远程学习者参与度评估指标研究
Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul;2018:307-310. doi: 10.1109/EMBC.2018.8512302.