Intelligent Wearable Systems for Occupational Risk Assessment and Prevention

The rapid advancement of intelligent wearable technologies is transforming occupational safety and health by enabling continuous, real-time assessment of workers, tasks, and work environments. Wearable devices equipped with physiological, biomechanical, environmental, and behavioral sensors, combined with advances in machine learning, artificial intelligence, and digital health technologies, provide unprecedented opportunities to identify hazards, quantify occupational risk, and support timely preventive actions across industries such as construction, manufacturing, healthcare, logistics, mining, transportation, and emergency response.Despite significant technological progress, important challenges remain in translating data into meaningful improvements in worker safety and health. Critical questions persist regarding sensor validity and reliability, algorithm performance and generalizability in real-world environments, human-centered design, worker acceptance, longitudinal effects of interventions, ethical deployment of systems, and the organizational strategies required to integrate wearable technologies into routine occupational safety practice.This Research Topic aims to bring together interdisciplinary research that advances the development, implementation, and evaluation of intelligent wearable technologies for occupational risk assessment and prevention. We welcome contributions in the areas of human factors and ergonomics, occupational safety and health, biomedical engineering, computer science, artificial intelligence (AI), public health, rehabilitation, and organizational sciences. Studies addressing diverse worker populations, ethical and regulatory considerations, equitable access to emerging technologies, and practical implementation in real-world occupational settings are particularly encouraged.We welcome submissions including, but not limited to:• Design, development and performance evaluation of wearable sensors for monitoring physiological, behavioral, biomechanical, and environmental factors in industrial environments.• Development of machine learning models for predicting physiological and cognitive states in workers and Artificial Intelligence (AI) for risk assessment and decision support.• Human factors in the design of wearable sensors and assistive devices.• User Interface Design for wearable interactive displays, Virtual and Augmented Reality based systems for improving worker situational awareness.• Hazard detection, anomaly detection, and predictive modeling for industrial workspaces.• Design and evaluation of new Personal Protective Equipment (PPE), industrial exoskeletons and collaborative robotics for occupational settings.• Interventions for promoting safety in human-automation shared workspaces and human-machine interaction.• Ethics, privacy, cybersecurity, governance, and regulatory considerations for continuous worker monitoring.• Digital health interventions and personalized approaches to occupational risk prevention and worker well-being. Topic editors: Pranav Madhav Kuber, Micaela Demichela Source: https://www.frontiersin.org/research-topics/86683/intelligent-wearable-systems-for-occupational-risk-assessment-and-prevention