Real-Time Sensor-Based and Self-Reported Emotional Perceptions of Urban Green-Blue Spaces: Exploring Gender Differences with FER and SAM.

ABSTRACT: Urban green-blue spaces (UGBS) are increasingly recognized for their benefits to physical and mental well-being. However, research on real-time gender-specific emotional responses to UGBS remains limited. To address this gap, a dual-method approach combining facial expression recognition (FER) and self-reported measures to investigate gender differences in real-time emotional evaluations of UGBS was developed. Using static images from Google Street View as stimuli, a self-reporting experiment involving 108 participants provided insights into subjective emotional experiences. Subsequently, a FER experiment, utilizing 360-degree video stimuli, captured over two million data points, validating the feasibility and advantages of real-time emotion monitoring. The findings revealed distinct gende

SUBMITTER: Zhang X 

PROVIDER: S-EPMC11820289 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature