Paper
28 August 2023 Study of fatigue driving based on face and physiological state
Fan Yang, Yuanhui Cui, Liu Yang
Author Affiliations +
Proceedings Volume 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023); 127242E (2023) https://doi.org/10.1117/12.2687492
Event: Second International Conference on Biomedical and Intelligent Systems (IC-BIS2023), 2023, Xiamen, China
Abstract
Various factors caused fatigue in driving and were difficult to determine by one aspect. Most of the current research was focused on the recognition of facial features under the fatigue state, ignoring the fact that fatigue is a slow process, which cannot be identified quickly and requires multi-angle monitoring to determine fatigue, and that little research has been conducted combining both facial and physiological states. Because of the intelligence of vehicle systems and the emergence of intelligence watches with physiological parameters, it is impossible to monitor fatigue from multiple angles and with less impact on the driver. In this paper, based on face tracking, Percentage of Eyelid Closure Over The Pupil Over Time(PERCLOS), Eye Aspect Ratio(EAR), Heart Rate Variability(HRV), Blood Oxygen Saturation(SO2), and Electrocardiogram(ECG). Based on a 2-hour highway experiment, facial features and physiological states were collected from three drivers driving for 12 hours. Finally, it was concluded that the recognition method of facial features and physiological states is superior to the single face recognition method. At the same time, the reference to time and frequency domain HRV parameters will detect fatigue in advance.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fan Yang, Yuanhui Cui, and Liu Yang "Study of fatigue driving based on face and physiological state", Proc. SPIE 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023), 127242E (28 August 2023); https://doi.org/10.1117/12.2687492
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KEYWORDS
Electrocardiography

Roads

Facial recognition systems

Intelligence systems

Cameras

Eye

Electroencephalography

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