Identifying stable EEG patterns over time for mental workload recognition using transfer DS-CNN framework-Reference-Cited by-同舟云学术

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Identifying stable EEG patterns over time for mental workload recognition using transfer DS-CNN framework

Published:2024-03 Issue: Volume:89 Page:105662
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Jin Lin^ORCID,Qu Hongquan^ORCID,Pang Liping^ORCID,Zhang Zheng^ORCID,Lyu Zhuoyang

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing,Biomedical Engineering

Reference55 articles.

1. Untersuchungen über den Grad der geistigen Beanspruchung;Bornemann;Arbeitsphysiologie,1942

2. Workload assessment in multi-task environments;Eggemeier,2020

3. Glenn F. Wilson, Operator Functional State Assessment for Adaptive Automation Implementation, in: John A. Caldwell, Nancy Jo Wesensten (Eds.), Defense and Security, Orlando, Florida, USA, 2005, p. 100.

4. The National Advanced Driving Simulator - Workload Measures;Miller,2001

5. A survey of workload assessment algorithms;Heard;IEEE Trans. Hum.-Mach. Syst.,2018

Cited by 2 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. Driver state recognition with physiological signals: Based on deep feature fusion and feature selection techniques;Biomedical Signal Processing and Control;2024-07

2. A Dual-Adversarial Model for Cross-Time and Cross-Subject Cognitive Workload Decoding;IEEE Transactions on Neural Systems and Rehabilitation Engineering;2024

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