Research Trends on Driver’s Drowsiness Detection Technology, and the Detection and the Control Using Facial Skin Temperature
Author:
Affiliation:
1. Faculty of Engineering and Design, Kagawa University
2. Management Science and Engineering Program, The University of Electro-Communications
3. College of Science and Engineering, Aoyama Gakuin University
Publisher
Japan Society for Fuzzy Theory and Intelligent Informatics
Link
https://www.jstage.jst.go.jp/article/jsoft/32/2/32_33/_pdf
Reference19 articles.
1. [1] 内閣府: 令和元年度版交通安全白書, 2019.
2. [2] M. Ramzan, H. U. Khan, S. M. Awan, A. Ismail, M. Ilyas, and A. Mahmood: “A Survey on State-of-the-Art Drowsiness Detection Techniques,” IEEE Access, Vol.7, pp. 61904-61919, 2019.
3. [3] R. Knipling and P. Rau: “PERCLOS:Avalid Psychophysiological Measure of Alertness as Assessed by Psychomotor Vigilance,” Federal Highway Administration, Vol.31, pp. 1237-1252, 1998.
4. [4] H. Choi, S. Min, S. Kim, H. Bae, J. Yoon, I. Hwang, D. Oh, C. Yun, and S. Yoon: “Learning-based Instantaneous Drowsiness Detection Using Wired and Wireless Electroencephalography,” IEEE Access, Vol.7, pp. 146390-146402, 2019.
5. [5] G. Li and W.-Y. Chung: “Detection of Driver Drowsiness using Wavelet Analysis of Heart Rate Variability and a Support Vector Machine Classifier,” Sensors, Vol.13, No.12, pp. 16494-16511, 2013.
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