Human thermal comfort indicator in high-temperature environments in deep mining

Abstract

With the continuous advancement of deep mining, high-temperature environments pose severe challenges to miners' thermal comfort and occupational health. This study systematically summarizes the primary analytical indicators for studying human thermal comfort in deep mining high-temperature environments, compares the advantages and limitations of existing models, and addresses the difficulty in dynamically measuring thermal comfort parameters. A novel wearable pulse monitoring device is proposed, utilizing easily trackable pulse parameters as a critical indicator of thermal comfort. The dynamic quantitative relationships between environmental temperature and physiological responses are analyzed, establishing a dynamic thermal comfort prediction framework based on pulse parameters. This method offers real-time feedback and enhanced accuracy in reflecting miners’ heat stress states. Results demonstrate that the proposed framework significantly outperforms traditional approaches in high-temperature conditions, providing theoretical and technical foundations for optimizing thermal environments, enhancing heat stress protection, and enabling intelligent mine safety management. Future research will integrate multi-source data fusion and multi-field coupling analysis to advance precision and intelligence in deep mining thermal comfort studies.