Key result
Classification algorithms based on electro-optical imaging systems successfully differentiated emotional and physical stress with an accuracy of over 90%.
Why the study?
Emotional stress status is typically intertwined with physical stress, making stress classification meaningful for practical health and security applications.
Electro-optical imaging systems using thermal and multispectral imaging can classify emotional versus physical stress with over 90% accuracy.
May enable non-invasive stress differentiation clinically; leaves open prospective validation in patient cohorts.
Emotional stress status is normally to be intertwined with physical stress information. It is meaningful to classify stress for real application such as homeland security and health. In this study, the classification algorithms are proposed based on electro-optical imaging system, such as thermal imaging (TI) system and multispectral imaging (MSI) system. Through the proposed model, the classification signals of ES and PS are successfully obtained. Experiments show that the classification result is encouraging, and the accuracy of the proposed algorithm is over 90%. This study can lead to a useful system for the stress classification and real applications. This research can lay a foundation for the application of stress recognition.
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Kan Hong (2022) studied Emotional and physical stress. Electro-optical imaging system algorithms was evaluated on Classification accuracy. Classification algorithms based on electro-optical imaging systems successfully differentiated emotional and physical stress with an accuracy of over 90%.
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