Physical fatigue is one of the major contributors to elevated serious injury risk, performance decline and long-term musculoskeletal disorders. In this session, you’ll learn about an AI-driven physical fatigue assessment framework that analyzes physiological and kinematic signals from a single wearable device to identify escalating fatigue risk, classify individualized fatigue levels and support proactive EHS decision-making. Drawing from recent research using multimodal data (heart rate, skin temperature, electrodermal activity and motion data), the session demonstrates how organizations can strengthen their EHS programs by incorporating objective fatigue indicators, emerging trend recognition and targeted preventive actions. You’ll gain practical guidance for implementing AI-supported fatigue management strategies that reduce exposure to serious injuries and fatalities; mitigate MSD progression; and promote safer, more sustainable worker performance.