TY - JOUR
T1 - Vision-Based Instant Measurement System for Driver Fatigue Monitoring
AU - Tsai, Yin Cheng
AU - Lai, Peng Wen
AU - Huang, Po Wei
AU - Lin, Tzu Min
AU - Wu, Bing Fei
N1 - Funding Information:
This work was supported in part by the Ministry of Science and Technology, Taiwan, under Grant MOST 108-2221-E-009-123-MY2.
Publisher Copyright:
© 2013 IEEE.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - biomedical monitoring
KW - Fatigue monitoring
KW - image sequence analysis
KW - remote photoplethysmography
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U2 - 10.1109/ACCESS.2020.2986234
DO - 10.1109/ACCESS.2020.2986234
M3 - Article
AN - SCOPUS:85084120958
SN - 2169-3536
VL - 8
SP - 67342
EP - 67353
JO - IEEE Access
JF - IEEE Access
M1 - 9058685
ER -