Abstract
In this paper, a vision-based physiological signal measurement system is proposed to instantly measure driver fatigue. A remote photoplethysmography (rPPG) signal is a type of physiological signal measured by a camera without any contact device, and it also retains the characteristics of the PPG, which is useful to evaluate fatigue. To solve the inconvenience caused by the traditional contact-based physiological fatigue detection system and to improve the accuracy, the system measures both the motional and physiological information by using one image sensor. In a practical application, the environmental noise would affect the measured signal, and therefore, we performed a preprocessing step on the signal to extract a clear signal. The experiment was designed in collaboration with Taipei Medical University, and a questionnaire-based method was used to define fatigue. The questionnaire that could directly react to the feeling of the subject was treated as our ground truth. The evaluated correlation was 0.89 and the root mean square error was 0.65 for ten-fold cross-validation on the dataset. The trend of driver fatigue could be evaluated without a contact device by the proposed system. This advantage ensures the safety of the driver and reliability of the system.
Highlights
Road traffic accidents have been predicted to be the third leading cause of death and disability in 2020 [1]
A remote photoplethysmography signal is a type of physiological signal measured by a camera without any contact device while retaining the characteristics of PPG
Considering all the complexities, we proposed a system to obtain the trend of the subject fatigue state with only one camera as the sensor
Summary
Road traffic accidents have been predicted to be the third leading cause of death and disability in 2020 [1]. Statistics show that driver fatigue is a contributing factor in numerous accidents and yearly approximately 20% of the total accidents are related to sleepiness [3]. To reduce these economic costs, finding a method to detect driver fatigue has become an important issue. A few years ago, vision-based methods were proposed to detect fatigue by capturing specific features with one or more cameras and image processing. In these methods, a driver monitor system captures the face of the driver and extracts features such as blinking, yawning, and the head movement of
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
