Regression analysis of facial thermal images for chronic stress estimation

Abstract

In recent years, the focus on mental health care in Japan has increased, leading to a rise in companies addressing employee mental well-being. Chronic stress, stemming from various sources including work and interpersonal relationships, can have severe impacts on individuals’ happiness and health. To address this, there is a growing demand for technology capable of measuring chronic stress on a daily basis. In this study, we explore the potential of using facial thermal images (FTI) as a method for daily measurement of chronic stress. We conducted experiments over a 3-month period with healthy adult participants, collecting routine data on chronic stress and capturing FTI. Independent component analysis (ICA) was applied to the FTI data to extract relevant features. In addition, psychological questionnaires were administered to assess chronic stress levels. We aggregated the questionnaire scores using principal component analysis (PCA) to obtain a single chronic stress indicator. Multiple regression analysis (MRA) was then employed to model the relationship between the extracted FTI components and chronic stress scores. Our results indicate a moderate to strong correlation between the predicted and actual chronic stress scores, suggesting the potential utility of FTI in estimating stress levels. Identified features in the FTI, particularly around the upper lip and on the right half of the face, showed significant associations with chronic stress. This study provides insights into the feasibility of using FTI as a non-invasive method for daily monitoring of chronic stress levels. However, limitations such as variations in stress levels among participants and questionnaire administration frequency should be considered in future research.