Detection of physical stress using multispectral imaging

Abstract This study explored the potential of multispectral imaging for detecting physical stress on humans. Multispectral images were obtained from recruited participants, and a max completion-based differential tissue oxygen saturation (StO2) algorithm model was proposed and established without background information. Further correlation analysis showed that multi-subject facial StO2 fluctuations have similar intra-class affective patterns under physical stress. The algorithm model was verified with respect to physical stress ground truth to classify the baseline and physical stress status. The algorithm implements non-contact, non-intervention, and background-free physical stress detection. The algorithm achieved promising results in the experiment with an accurate rate of higher than 90%, which will provide an excellent foundation for future industrialization. Experimental results demonstrated that multispectral imaging, as a non-invasive method, has the potential to identify physical stress on humans.