Skip to main content
SpringerLink
Log in

A PERCLOS Method for Fine Characterization of Behaviour Circadian Rhythm

  • Conference paper
  • First Online:
Man-Machine-Environment System Engineering (MMESE 2020)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 645))

Included in the following conference series:

Abstract

Objective To establish a measurement method of the percentage of eyelid closure over the pupil over time (PERCLOS) to finely characterize behaviour circadian rhythm. Methods A computer program was designed based on multitask convolutional neural network for the treatment of videos to get PERCLOS quantitative values. 7 volunteers were recruited in this research. The volunteers were asked to face the personal computers and play a simple game for 5 min, doing the test 4 times a day that was just after getting up in the morning, at noon, in the evening and just before going to bed. Their videos were recorded and treated with the computer program to obtain PERCLOS results. The results showed that the PERCLOS values of 6 young persons increased from morning to night in accordance with the circadian rhythm of youth, while an elder female volunteer showed a different circadian rhythm from that of the youth. Conclusions The PERCLOS method for characterization of behaviour circadian rhythm was successfully developed, which would serve as effective tool for circadian rhythm related studies.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ledford H, Callaway E (2017) Circadian clocks scoop Nobel prize. Nature 55:18

    Article  Google Scholar 

  2. Gau SS, Shang CY, Merikangas KR et al (2007) Association between morningness-eveningness and behavioral/emotional problems among adolescents. J Biol Rhythms 22:268–274

    Article  Google Scholar 

  3. Escobar C, Salgado R, Rodriguez K et al (2011) Scheduled meals and scheduled palatable snacks synchronize circadian rhythms: consequences for ingestive behavior. Physiol Behav 104:555–561

    Article  Google Scholar 

  4. Hofstra WA, Weerd AW (2008) How to assess circadian rhythm in humans: a review of lit erature. Epilepsy Behav 13:438–444

    Article  Google Scholar 

  5. Ngxande M, Tapamo J-R, Bruke M (2017) Driver drowsiness detection using behavioural measures and machine learning techniques: a review of state-of-art techniques. 2017 Pattern recognition association of south Africa and robotics and mechatronics (PRASA-RobMech), 156–160. https://doi.org/10.1109/robomech.2017.8261140

  6. Ergun H, Sert M (2016) Fusing deep convolutional networks for largescale visual concept classification. In 2016 IEEE second international conference on multimedia big data (BigMM). IEEE. pp 210–213

    Google Scholar 

  7. Den R, Toda M, Nagasawa S et al (2007) Circadian rhythm of human salivary chromogranin A. Biomed Res 28:57–60

    Article  Google Scholar 

  8. Carrier J, Monk TH (2000) Circadian rhythms of performance: new trends. Chronobiol Inter 17:719–732

    Article  Google Scholar 

  9. Dinges D, Grace R (1998) PERCLOS: a valid psychophysiological measure of alertness as assessed by psychomotor vigilance. Tech Rep No FHWA-MCRT-98–006

    Google Scholar 

  10. May JF, Baldwin CL (2009) Driver fatigue: the importance of identifying causal factors of fatigue when considering detection and countermeasure technologies. Transport Res Part F 12:218–224

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledge the financial support of the Sichuan Science and Technology Program, under grant 2019YFG0390, Safety Foundation of Civil Aviation Administration of China and the Joint Funds of the National Natural Science Foundation of China (No. U1333132).

Compliance with Ethical Standards

The study was approved by the Logistics Department for the Civilian Ethics Committee of the Second Institute of Civil Aviation Administration of China. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

Author information

Authors and Affiliations

  1. The Second Research Institute of Civil Aviation Administration of China, 610041, Chengdu, China

    Yanzhong Gu, Zhenling Chen, Jianping Zhang, Pengxin Ding & Weinan Deng

  2. Civil Aviation Flight, University of China, 618307, Guanghan, China

    Yanzhong Gu & Weinan Deng

  3. Civil Aviation Medicine Center, Civil Aviation Administration of China (Civil Aviation Hospital), 100123, Beijing, China

    Zhenling Chen

  4. Air Traffic Management Regulation Office, Civil Aviation Administration of China, 10071, Beijing, China

    Guoliang Zou

  5. College of Computer Science, Sichuan University, 610056, Chengdu, China

    Pengxin Ding

Authors
  1. Yanzhong Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhenling Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jianping Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Guoliang Zou
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Pengxin Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Weinan Deng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jianping Zhang .

Editor information

Editors and Affiliations

  1. Astronaut Research and Training Center of China, Beijing, China

    Shengzhao Long

  2. Department of Mechanical Engineering, University of Ottawa, Ottawa, ON, Canada

    Balbir S. Dhillon

Rights and permissions

Reprints and permissions

Copyright information

© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Gu, Y., Chen, Z., Zhang, J., Zou, G., Ding, P., Deng, W. (2020). A PERCLOS Method for Fine Characterization of Behaviour Circadian Rhythm. In: Long, S., Dhillon, B.S. (eds) Man-Machine-Environment System Engineering. MMESE 2020. Lecture Notes in Electrical Engineering, vol 645. Springer, Singapore. https://doi.org/10.1007/978-981-15-6978-4_30

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-6978-4_30

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-6977-7

  • Online ISBN: 978-981-15-6978-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation