Study on identification method of driver fatigue considering individual ECG differences-Reference-Cited by-同舟云学术

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Study on identification method of driver fatigue considering individual ECG differences

Published:2024-03-27 Issue:2 Volume:26 Page:301-312
ISSN:1435-5558
Container-title:Cognition, Technology & Work
language:en
Short-container-title:Cogn Tech Work

Author:

Sun Wencai,Jiang Wei,Li Chen,Si Yihao,Li Shiwu,Guo Mengzhu,Liu Dezhi,Song Huijun

Funder

National Key R&D Program of China

Youth Program of National Natural Science Foundation of China

the Transportation Innovation and Development Support Project of Jilin Province

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10111-024-00755-9.pdf

Reference23 articles.

1. Alam L, Hoque MM (2018) Vision-based driver’s attention monitoring system for smart vehicles. International Conference on Intelligent Computing & Optimization. Springer, Cham, pp. 196–209

2. Balandong RP, Ahmad RF, Saad MNM et al (2018) A review on EEG-based automatic sleepiness detection systems for driver. IEEE Access 6:22908–22919

3. Balasubramanian V, Adalarasu K (2007) EMG-based analysis of change in muscle activity during simulated driving. J Bodyw Mov Ther 11(2):151–158

4. Casal R, Di Persia LE, Schlotthauer G (2019) Sleep-wake stages classification using heart rate signals from pulse oximetry. Heliyon 5(10):e02529

5. Chowdhury A, Shankaran R, Kavakli M et al (2018) Sensor applications and physiological features in drivers’ drowsiness detection: a review. IEEE Sens J 18(8):3055–3067

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