Applied Sciences (Apr 2022)

Contactless Vital Sign Monitoring System for In-Vehicle Driver Monitoring Using a Near-Infrared Time-of-Flight Camera

  • Kaiwen Guo,
  • Tianqu Zhai,
  • Manoj H. Purushothama,
  • Alexander Dobre,
  • Shawn Meah,
  • Elton Pashollari,
  • Aabhaas Vaish,
  • Carl DeWilde,
  • Mohammed N. Islam

DOI
https://doi.org/10.3390/app12094416
Journal volume & issue
Vol. 12, no. 9
p. 4416

Abstract

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We demonstrate a Contactless Vital Sign Monitoring (CVSM) system and road-test the system for in-cabin driver monitoring using a near-infrared indirect Time-of-Flight (ToF) camera. The CVSM measures both heart rate (HR) and respiration rate (RR) by leveraging the simultaneously measured grayscale and depth information from a ToF camera. For a camera-based driver monitoring system (DMS), key challenges from varying background illumination and motion-induced artifacts need to be addressed. In this study, active illumination and depth-based motion compensation are used to mitigate these two challenges. For HR measurements, active illumination allows the system to work under various lighting conditions, while our depth-based motion compensation has the advantage of directly measuring the motion of the driver without making prior assumptions about the motion artifacts. In addition, we can extract RR directly from the chest wall motion, circumventing the challenge of acquiring RR from the near-infrared photoplethysmography (PPG) signal of low signal quality. We investigate the system’s performance in various scenarios, including monitoring both drivers and passengers while driving on highways and local roads. Our results show that our CVSM system is ambient light agnostic, and the success rates of HR measurements on the highway are 82% and 71.9% for the passenger and driver, respectively. At the same time, we show that the system can measure RR on users driving on a highway with a mean deviation of −1.4 breaths per minute (BPM). With reliable HR and RR measurement in the vehicle, the CVSM system could one day be a key enabler to sudden sickness or drowsiness detection in DMS.

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