Discrimination of Stress-Coping Styles Based on Near-Infrared Facial Images Using Sparse Modeling

Abstract

Drivers show two types of stress-coping responses: active coping responses to stressful stimuli that they actively cope with and passive coping responses to stressful stimuli that they have no choice but to endure. Considering that the two types of stress-coping styles of drivers can be used as indicators of safety and comfort evaluation at all SAE levels, a method must be established to distinguish between them. Stress-coping styles can be distinguished based on hemodynamic variability; however, existing hemodynamic measurement methods require contact and time. In this study, we measured facial skin blood flow using a noncontact method by capturing near-infrared facial images using near-infrared light, which has a high depth of penetration into biological tissues. Furthermore, we applied sparse modeling, an information extraction technique, to near-infrared facial images to extract skin blood flow features related to stress-coping styles and attempted to distinguish stress-coping styles as quickly as possible using a single image. Consequently, we identified skin blood flow characteristics of the nasal apex and cheeks related to stress-coping styles and developed a noncontact, rapid discrimination method with an accuracy of 83.1%。