Monitoring the Variation in Driver Respiration Rate from Wakefulness to Drowsiness: A Non-Intrusive Method for Drowsiness Detection Using Thermal Imaging

  • Serajeddin Ebrahimian Hadi Kiashari Department of Mechatronics Engineering, School of Mechanical Engineering, K.N.Toosi University of Technology, Tehran, Iran
  • Ali Nahvi Department of Mechatronics Engineering, School of Mechanical Engineering, K.N.Toosi University of Technology, Tehran, Iran
  • Amirhossein Homayounfard Department of Mechatronics Engineering, School of Mechanical Engineering, K.N.Toosi University of Technology, Tehran, Iran
  • Hamidreza Bakhoda Department of Mechatronics Engineering, School of Mechanical Engineering, K.N.Toosi University of Technology, Tehran, Iran
Keywords: Sleep, Respiration, Automobile driving, Thermography

Abstract

Background and Objective: Driver drowsiness is a cause of many traffic accidents all around the world. Driver respiration dynamics undergoes significant changes from wakefulness to sleep. The intrusive nature of current respiration monitoring methods makes them unattractive for detection of in-vehicle driver drowsiness. In this paper, changes in the respiration rate were monitored for drowsiness detection using thermal imaging, which is completely contact-free and non-intrusive.

Materials and Methods: For each frame, the driver’s face was isolated from the rest of the image. Then, the nostrils' zone was localized using physiological characteristics of face. The respiration signal was constructed by putting together the mean temperature of nostril region in all of the frames. In order to study respiration variations from wakefulness to drowsiness, a total number of 12 subjects were tested in a driving simulator. The observer rating of drowsiness (ORD) method was used to estimate the drowsiness level of the subjects.

Results: Derivation of driver respiration rate using thermal imaging was a reliable and non-intrusive method. The results were strongly correlated with those of traditional methods. Driver respiration rate decreased from wakefulness to extreme drowsiness by 3.5 breaths per minute (bpm) and its standard deviation (SD) increased by 0.7 bpm.

Conclusion: Driver respiration rate decreased and its SD increased from wakefulness to drowsiness in 12 participants of this study. The results showed that driver drowsiness could be detected even at moderate levels from analysis of the respiration rate.

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Published
2019-01-07
How to Cite
1.
Ebrahimian Hadi Kiashari S, Nahvi A, Homayounfard A, Bakhoda H. Monitoring the Variation in Driver Respiration Rate from Wakefulness to Drowsiness: A Non-Intrusive Method for Drowsiness Detection Using Thermal Imaging. J Sleep Sci. 3(1-2):1-9.
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Original Article(s)