Integrating Machine Learning and Wearable Technology to Prevent Musculoskeletal Injuries in Military Training: A Natural Science Approach

Rita Komalasari(1*), Cecep Mustafa(2),

(1) Department of Public Health, Faculty of Medicine, YARSI University, Jakarta
(2) Department of Public Health, Faculty of Medicine, YARSI University, Jakarta
(*) Corresponding Author


Musculoskeletal injuries remain a substantial challenge in military training programs worldwide, undermining both operational readiness and soldier well-being. This paper explores the potential of an innovative approach to address this issue by integrating machine learning and wearable technology within the framework of natural sciences. The purpose of this study is to develop a comprehensive model capable of predicting and preventing musculoskeletal injuries in military personnel. The design/methodology/approach involves blending principles from biomechanics, physiology, kinesiology, and anatomy to create a predictive model, fueled by real-time data collected through wearable technology. This data is then analyzed using machine learning techniques to generate insights for injury prevention. The results showcase the viability of such an approach, offering the prospect of significantly reducing injuries and enhancing military preparedness. By revolutionizing injury prevention strategies through an interdisciplinary approach, this study underscores the potential to create a paradigm shift in safeguarding the physical health of military personnel on a global scale.


Musculoskeletal Injuries; Military Training; Natural Sciences; Wearable Technology; Machine Learning

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