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Volume 50 Issue 9
Sep.  2024
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Journal of Beijing University of Aeronautics and Astronautics  > 2024  >  50(9): 2753-2762.
LI J Q，FANG Q，FAN T C，et al. Fatigue detection of facial 3D physiological feature points in sleep deprivation[J]. Journal of Beijing University of Aeronautics and Astronautics，2024，50（9）：2753-2762 （in Chinese） doi: 10.13700/j.bh.1001-5965.2022.0733
Citation: LI J Q，FANG Q，FAN T C，et al. Fatigue detection of facial 3D physiological feature points in sleep deprivation[J]. Journal of Beijing University of Aeronautics and Astronautics，2024，50（9）：2753-2762 （in Chinese） doi: 10.13700/j.bh.1001-5965.2022.0733
shu

Fatigue detection of facial 3D physiological feature points in sleep deprivation

doi: 10.13700/j.bh.1001-5965.2022.0733
  • 1.

    College of Safety Science and Engineering，Civil Aviation University of China，Tianjin 300300，China

  • 2.

    Research Institute of Civil Aviation Safety，Civil Aviation University of China，Tianjin 300300，China

  • 3.

    Sino-European Institute of Aviation Engineering，Civil Aviation University of China，Tianjin 300300，China

Funds:  National Natural Science Foundation of China (U1933122); The Fundamental Research Funds for the Central Universities (3122019186)
More Information
  • Corresponding author: E-mail：jqli@cauc.edu.cn
  • Received Date: 20 Aug 2022
  • Accepted Date: 03 Feb 2023
    • Available Online: 10 Mar 2023
  • Publish Date: 09 Mar 2023
    Abstract

  • Sleep deprivation and circadian rhythm disorder are important factors affecting the fatigue of transportation staff. In order to advance the safety risk prevention threshold, it is now vital to identify staff fatigue concurrently with the advent of "face brushing" technology while on duty. This study uses the 30 h sleep deprivation experiment to further explore the three-dimensional changes of facial fatigue. Based on the fusion of facial bilateral curvature characteristics and principal component analysis (PCA), it proposes the wrinkles severity index (WSI), which when paired with the objective heart rate (HR) monitoring method, psychomotor vigilance test, and subjective fatigue assessment, integrated subjects' facial fatigue judgment. The results showed that under the condition of sleep deprivation, the WSI changes and fatigue fluctuated significantly, and the overall trend was gradually increasing. The results of the 30 h trial revealed a high correlation between the change in WSI and the trends in subjective tiredness index, response time (P<0.01), and HR (P<0.05). Based on the WSI index, the fatigue was divided into four grades, and the feasibility of static detection of facial fatigue was verified from the perspective of three-dimensional physiological characteristics. The results provided a new idea for rapid fatigue detection technology.

     

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