Fatigue State Detection for Tired Persons in Presence of Driving Periods-Reference-Cited by-同舟云学术

Fatigue State Detection for Tired Persons in Presence of Driving Periods

Published:2022 Issue: Volume:10 Page:79403-79418
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Alharbey Riad¹^ORCID,Dessouky Mohamed M.²,Sedik Ahmed³^ORCID,Siam Ali I.⁴^ORCID,Elaskily Mohamed A.⁵^ORCID

Affiliation:

1. Department of Information System and Technology, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia

2. Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia

3. Department of the Robotics and Intelligent Machines, Faculty of Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh, Egypt

4. Department of Embedded Network Systems Technology, Faculty of Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh, Egypt

5. Department of Informatics, Electronics Research Institute (ERI), Cairo, Egypt

Funder

University of Jeddah, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09802993.pdf?arnumber=9802993

Reference33 articles.

1. A multimodal approach to estimating vigilance using EEG and forehead EOG

2. A Framework for Instantaneous Driver Drowsiness Detection Based on Improved HOG Features and Naïve Bayesian Classification

3. An Investigation of Early Detection of Driver Drowsiness Using Ensemble Machine Learning Based on Hybrid Sensing

4. Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG

5. Driver drowsiness monitoring based on yawning detection

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