China Safety Science Journal ›› 2026, Vol. 36 ›› Issue (1): 191-198.doi: 10.16265/j.cnki.issn1003-3033.2026.01.0868

• Public Safety and Emergency Management • Previous Articles     Next Articles

Differences in stress-induced emotional responses to sudden accidents based on facial expression recognition

MENG Junqing1(), FU Yunlian1, GAO Bin2, QIU Jingyuan1   

  1. 1 School of Emergency Management and Safety Engineering,China University of Mining & Technology (Beijing), Beijing 100083,China
    2 Liaocheng Urban and Rural Planning and Design Institute, Liaocheng Shandong 252000, China
  • Received:2025-09-10 Revised:2025-11-20 Online:2026-02-08 Published:2026-07-28

Abstract:

In order to explore the emotional expression characteristics of different types of groups under emergencies, and to deeply analyze the influence of gender, temperament type and accident environment on the stress state emotions of the groups, a stress state emotional stimulation test based on facial expression technology was designed. A cohort of 137 participants was exposed to five categories of accident videos. Facial expression data for six basic emotions were collected using FaceReader software, with the Kruskal-Wallis test employed to analyze differences across gender, temperament types, and accident scenarios. A k-means clustering model was further constructed based on arousal dynamic features. The results show that female participants exhibit significantly higher intensities of sadness and fear, whereas males show stronger anger responses. Sanguine individuals demonstrate the most pronounced emotional reactivity, while phlegmatic types achieve the fastest arousal modulation. Fear responses are most pronounced in building fire scenarios. Males outperform females in arousal self-regulation capacity.

Key words: facial expression recognition, sudden accident, stress state, emotional response, k-means clustering

CLC Number: