Detection of physical stress using multispectral imaging
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...
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| Published in | Neurocomputing (Amsterdam) Vol. 329; pp. 116 - 128 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
15.02.2019
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0925-2312 1872-8286 |
| DOI | 10.1016/j.neucom.2018.10.011 |
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| 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. |
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| AbstractList | 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. |
| Author | Liu, Xiaoling Liu, Guodong Hong, Kan Chen, Wentao |
| Author_xml | – sequence: 1 givenname: Kan surname: Hong fullname: Hong, Kan email: 16451946@qq.com organization: Optoelectronics and Communication Engineering Key Laboratory, Jiangxi Science and Technology Normal University, Nanchang, China – sequence: 2 givenname: Xiaoling surname: Liu fullname: Liu, Xiaoling organization: Provincial surveying & mapping production archives of Hubei, China – sequence: 3 givenname: Guodong surname: Liu fullname: Liu, Guodong organization: Optoelectronics and Communication Engineering Key Laboratory, Jiangxi Science and Technology Normal University, Nanchang, China – sequence: 4 givenname: Wentao surname: Chen fullname: Chen, Wentao organization: Weibo Internet Technology (China) Co. Ltd, Beijing, China |
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