StressCam: non-contact measurement of users' emotional states through thermal imaging
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Imaging Facial Physiology for the Detection of Deceit
International Journal of Computer Vision
Computer Vision and Image Understanding
Detecting stress during real-world driving tasks using physiological sensors
IEEE Transactions on Intelligent Transportation Systems
Queueing network modeling of human performance of concurrent spatial and verbal tasks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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This paper describes research that aims to quantify stress levels of operators who perform multiple tasks. The proposed method is based on the thermal signature of the face. It measures physiological function from a stand-off distance and therefore, it can unobtrusively monitor a machine operator. The method was tested on 11 participants. The results show that multi-tasking elevates metabolism in the supraorbital area, which is an indirect indication of increased mental load. This local metabolic change alters heat dissipation and thus, it can be measured through thermal imaging. The methodology could serve as a benchmarking tool in scenarios where an operator's divided attention may cause harmful outcomes. A classic example is the case of a vehicle driver who talks on the cell phone. This stress measurement method when combined with user performance metrics can delineate optimal operational envelopes.