EEG-Based Mental Workload Classification Method Based on Hybrid Deep Learning Model Under IoT-Reference-Cited by-同舟云学术

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EEG-Based Mental Workload Classification Method Based on Hybrid Deep Learning Model Under IoT

Published:2023 Issue: Volume: Page:1-10
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Shao Shiliang¹^ORCID,Han Guangjie²^ORCID,Wang Ting¹,Lin Chuan³^ORCID,Song Chunhe¹^ORCID,Yao Chen¹

Affiliation:

1. State Key Laboratory of Robotics, Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang, China

2. Department of Internet of Things Engineering, Hohai University, Changzhou, China

3. Software College, Northeastern University, Shenyang, China

Funder

Applied Basic Research Program of Liaoning Province

National Science Foundation of China

Independent Project of the State Key Laboratory of Robotics

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/6363502/10143538.pdf?arnumber=10143538

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Guest Editorial AI-Empowered Internet of Things for Data-Driven Psychophysiological Computing and Patient Monitoring;IEEE Journal of Biomedical and Health Informatics;2024-05

2. Integration of Structural Equation Models and Bayesian Networks for Cognitive Load Modeling;2023 IEEE Symposium Series on Computational Intelligence (SSCI);2023-12-05

3. Cognitive Workload Classification in Industry 5.0 Applications: Electroencephalography-Based Bi-Directional Gated Network Approach;Electronics;2023-09-23

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