An EEG Channel Selection Framework for Driver Drowsiness Detection via Interpretability Guidance-Reference-Cited by-同舟云学术

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An EEG Channel Selection Framework for Driver Drowsiness Detection via Interpretability Guidance

Published:2023-07-24 Issue: Volume: Page:
ISSN:
Container-title:2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Zhou Xinliang¹,Lin Dan²,Jia Ziyu³,Xiao Jiaping⁴,Liu Chenyu¹,Zhai Liming²,Liu Yang¹

Affiliation:

1. Nanyang Technological University,School of Computer Science and Engineering,Singapore,639798

2. Nanyang Technological University,Continental-NTU Corporate Lab,Singapore,639798

3. Chinese Academy of Sciences,Brainnetome Center, Institute of Automation,Beijing,China,100190

4. Nanyang Technological University,School of Mechanical and Aerospace Engineering,Singapore,639798

Funder

National Research Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10339936/10339939/10341126.pdf?arnumber=10341126

Reference23 articles.

1. Road safety thematic report – fatigue;Commission;Tech. Rep., European Road Safety Observatory,2021

2. AN IMPROVED AND PORTABLE EYE-BLINK DURATION DETECTION SYSTEM TO WARN OF DRIVER FATIGUE

3. Applying neural network analysis on heart rate variability data to assess driver fatigue

4. Development of Drowsiness Detection System Based on Respiration Changes Using Heart Rate Monitoring

5. Driver fatigue detection based on deeply-learned facial expression representation

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1. Low-carbon innovation efficiency of high-tech industries and its influencing factors;International Journal of Low-Carbon Technologies;2024

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