Introduction: Industry 5.0 mandates human-centric and resilient manufacturing ecosystems, yet occupational burnout remains a critical challenge. Traditional burnout detection relies on lengthy and retrospective instruments that induce severe assessment fatigue and recall bias, making them difficult to scale seamlessly in fast-paced industrial environments. To bridge this critical structural gap, we introduce a frictionless mobile assistive framework based on human-integrated artificial intelligence for intelligent burnout management. By transforming rigid psychological evaluations into rapid and interactive wellness check-ins, it uses everyday smartphones as proactive monitoring tools that capture integrated biometrics without disrupting occupational workflows.
Methods: We developed a human-integrated AI architecture synergizing multimodal objective photoplethysmography (PPG) biometrics and subjective perception from brief self-reports into a unified intelligence model. The system implements a dynamic and weighted algorithm consisting of a quick digital check-in, PPG-derived markers, and inter-session trend analysis. We conducted pilot validation systematically benchmarked against the Maslach Burnout Inventory (MBI) as a gold standard to classify occupational burnout.
Results and Conclusions: The program achieved robust diagnostic performance with a test ROC-AUC of 0.95. By effectively synergizing physiological sensing with burnout perception through a micro-assessment interface, this system has the potential to overcome the structural bottlenecks and assessment fatigue of traditional occupational monitoring. While current findings rely on limited pilot implementation, they establish a definitive foundation for forthcoming large-scale deployments across diverse industries. It has the potential to fundamentally transform workplace well-being and provide an intelligent burnout management infrastructure essential for realizing the resilient and human-centric vision of Industry 5.0.