Abstract: One factor that has a positive correlation with the risk of traffic accidents is the pain experienced by drivers. This pain is sometimes expressed facially by the driver and can be subjectively perceived by others. By observing the facial expression of drivers, it can estimate the pain experienced at that point in time and intervene to prevent some accidents. A method to automatically estimate the pain level expressed by a driver using their facial expression will be proposed in this study. The model is trained by a convolution neural network based on a public dataset of facial expressions at various pain levels. This model is then used to automatically classify the pain level perceived using only the facial expressions of drivers. The result of the automated classification is then compared to ratings of subjective feelings of the driver’s pain evaluated by a medical doctor. The experiment results showed that the model classified the pain level expressed facially by the drivers matched that of the classification by the medical doctor at a rate of 80%.

F. Hadi, O. Fukuda, W. LYeoh, H. Okumura, Y. Rodiah, Herlina and A. Prasetyo, “Automated Subjective Perception of a Driver’s Pain Level Based on Their Facial Expression” International Journal of Advanced Computer Science and Applications(IJACSA), 16(2), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160208

@article{Hadi2025,
title = {Automated Subjective Perception of a Driver’s Pain Level Based on Their Facial Expression},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160208},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160208},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {2},
author = {F. Hadi and O. Fukuda and W. LYeoh and H. Okumura and Y. Rodiah and Herlina and A. Prasetyo}
}