de Vries Herman J, van der Wal Sija J, Delahaij Roos, Venrooij Ward, Kamphuis Wim
Department of Learning and Workforce Development, Netherlands Organisation for Applied Scientific Research (TNO), Soesterberg, Netherlands.
Department of Human Machine Teaming, Netherlands Organisation for Applied Scientific Research (TNO), Soesterberg, Netherlands.
Front Digit Health. 2025 May 7;7:1542140. doi: 10.3389/fdgth.2025.1542140. eCollection 2025.
Military personnel face significant physical and mental demands, making continuous physiological monitoring essential for understanding health status, managing long-term health risks, and predicting a soldier's readiness to perform in military operations. Recent advancements in wearable technology enable the tracking of biomarkers and psychophysiological indicators, yet current approaches remain fragmented, often focusing on isolated health outcomes rather than comprehensive, actionable insights. This perspective article reviews overarching theoretical health models and examines statistical modeling approaches to better capture the multidimensional nature of health and readiness. Building on these insights, a vision is presented for developing a military health and readiness monitoring system that integrates wearable technology with tailored health indicators and outcomes, aligned with the specific demands of military tasks. The role of advanced tools, such as Large Language Models (LLMs) and Knowledge Graphs in contextualizing health data with operational demands is highlighted, offering a pathway to more accurate and actionable assessments of readiness. This vision outlines key considerations for future development, aiming to empower service members and military leadership with effective tools for health and readiness management.
军事人员面临着巨大的身心需求,因此持续进行生理监测对于了解健康状况、管理长期健康风险以及预测士兵在军事行动中的作战准备状态至关重要。可穿戴技术的最新进展使得对生物标志物和心理生理指标的跟踪成为可能,但目前的方法仍然零散,往往侧重于孤立的健康结果,而非全面、可采取行动的见解。这篇观点文章回顾了总体的理论健康模型,并研究了统计建模方法,以更好地把握健康和作战准备状态的多维性质。基于这些见解,本文提出了一个愿景,即开发一个军事健康和作战准备状态监测系统,该系统将可穿戴技术与量身定制的健康指标和结果相结合,以符合军事任务的特定需求。文中强调了大型语言模型(LLMs)和知识图谱等先进工具在根据作战需求对健康数据进行情境化处理方面的作用,为更准确、可采取行动的作战准备状态评估提供了一条途径。这一愿景概述了未来发展的关键考虑因素,旨在为军人和军事领导层提供有效的健康和作战准备状态管理工具。