Driver Fatigue Detection

Abdullah, Muhamad Hafiz; Raman, Kirbana Jai; Azman, Azreen; Yogarayan, Sumendra; Elbendary, Hesham Ali Alsayed; Abdullah, Mohd Fikri Azli; Ibrahim, Siti Zainab

doi:10.1007/978-981-10-0557-2_27

Cited by 4 publications

(2 citation statements)

References 3 publications

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“…to the aspect ratio of the eye region, which is often used to calculate the temporal consistency and speed of left and right eye blinks [12] and in fatigue detection [11,[13][14][15]. ere has been no report of the application of EAR to the objective assessment of facial paralysis.…”

Section: Calculation Of the Difference In Bilateral Ear Ear Refersmentioning

confidence: 99%

Using Eye Aspect Ratio to Enhance Fast and Objective Assessment of Facial Paralysis

Feng

Guo

Wang

et al. 2020

Computational and Mathematical Methods in Medicine

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A rapid and objective assessment of the severity of facial paralysis allows rehabilitation physicians to choose the optimal rehabilitation treatment regimen for their patients. In this study, patients with facial paralysis were enrolled as study objects, and the eye aspect ratio (EAR) index was proposed for the eye region. The correlation between EAR and the facial nerve grading system 2.0 (FNGS 2.0) score was analyzed to verify the ability of EAR to enhance FNGS 2.0 for the rapid and objective assessment of the severity of the facial paralysis. Firstly, in order to accurately calculate the EAR, we constructed a landmark detection model based on the face images of facial paralysis patients (FP-FLDM). Evaluation results showed that the error rate of facial feature point detection in patients with facial paralysis of FP-FLDM is 17.1%, which was significantly superior to the landmark detection model based on normal face images (NF-FLDM). Secondly, in this study, the Fréchet distance was used to calculate the difference in bilateral EAR of facial paralysis patients and to verify the correlation between this difference and the corresponding FNGS 2.0 score. The results showed that the higher the FNGS 2.0 score , the greater the difference in bilateral EAR. The correlation coefficient between the bilateral EAR difference and the corresponding FNGS 2.0 score was 0.9673, indicating a high correlation. Finally, through a 10-fold crossvalidation, we can know that the accuracy of scoring the eyes of patients with facial paralysis using EAR was 85.7%, which can be used to enhance the objective and rapid assessment of the severity of facial paralysis by FNGS 2.0.

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Section: Calculation Of the Difference In Bilateral Ear Ear Refersmentioning

confidence: 99%

Using Eye Aspect Ratio to Enhance Fast and Objective Assessment of Facial Paralysis

Feng

Guo

Wang

et al. 2020

Computational and Mathematical Methods in Medicine

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“…Attention assist system equipped with Benz [38], which uses 71 sensors to collect parameters of vehicle steering wheel angle, acceleration, accelerator pedal, brake pedal and various external environmental parameters. These parameters are used to conduct a scientific analysis of the driver's driving behavior.…”

Section: Application Of Fatigue Driving Detection Technologymentioning

confidence: 99%

A Review on Fatigue Driving Detection

Shi

Wang

2017

ITM Web Conf.

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Abstract:The socialization of automobile development has brought great convenience to people's travel. However, the rapid increase in the number of vehicles has also caused a series of problems. The increase in traffic accidents has brought great social casualties and economic losses. Fatigue driving, which is an important factor in the traffic accident, has aroused people's attention. This paper reviews all kinds of fatigue driving detection methods at present; compares various fatigue driving detection methods in terms of accuracy, real-time and cost; analyses the advantages and disadvantages of various methods; introduces the application of fatigue detection system in automobile; summarizes the current deficiencies and future development trends in the field of fatigue driving detection. The future research of this field will be more to the data fusion, computer vision and deep learning.

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Estimation of the interrelation between the pilot state and the quality index of piloting

Корсун

Yurko

et al. 2022

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Driver Fatigue Detection

Cited by 4 publications

References 3 publications

Using Eye Aspect Ratio to Enhance Fast and Objective Assessment of Facial Paralysis

Using Eye Aspect Ratio to Enhance Fast and Objective Assessment of Facial Paralysis

A Review on Fatigue Driving Detection

Estimation of the interrelation between the pilot state and the quality index of piloting

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