Abstract: Method for thermal pain level prediction with eye motion using SVM is proposed. Through experiments, it is found that thermal pain level is much sensitive to the change rate of pupil size rather than pupil size itself. Also, it is found that the number of blinks shows better classification performance than the other features. Furthermore, the eye size is not a good indicator for thermal pain. Moreover, it is also found that user respond to the thermal stimulus so quickly (0 to 3 sec.) while the thermal pain is remaining for a while (4 to 17 sec.) after the thermal stimulus is removed.

Kohei Arai, “Method for Thermal Pain Level Prediction with Eye Motion using SVM” International Journal of Advanced Computer Science and Applications(IJACSA), 9(4), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090427

@article{Arai2018,
title = {Method for Thermal Pain Level Prediction with Eye Motion using SVM},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090427},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090427},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {4},
author = {Kohei Arai}
}