@inproceedings{986126a306b948cc91602463e5d3e49b,
title = "A contactless sport training monitor based on facial expression and remote-ppg",
abstract = "To successfully increase athletes' or exercisers' fitness and endurance, the factors of physiological signal, emotion, or the level of fatigue should be considered during the training program. Many clinical decision support systems can assist to monitor the exercisers by some wearable devices. And, the questionnaire should also be taken into account to produce a report. Such process is cumbersome, and the results are not objective. Furthermore, one may feel uncomfortable when wearing the devices during the training program. In this research, the Rating of Perceived Exertion (RPE) is expected to be estimated automatically without any wearable devices and questionnaires. A camera based heart rate detection algorithm nd a fatigue expression feature extractor are fused to estimate the RPE value. The results show that our heart rate detection algorithm can be competitive to the wearable devices, and the trend of the detected heart rate is correlated to RPE. Moreover, the fatigue feature can help reduce the error of the estimation.",
keywords = "Clinical decision support system, Facial expression recognition, Heart rate detection",
author = "Bing-Fei Wu and Lin, {Chun Hsien} and Huang, {Po Wei} and Lin, {Tzu Min} and Chung, {Meng Liang}",
year = "2017",
month = nov,
day = "27",
doi = "10.1109/SMC.2017.8122715",
language = "English",
series = "2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "846--851",
booktitle = "2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017",
address = "United States",
note = "null ; Conference date: 05-10-2017 Through 08-10-2017",
}