Collaborative Simulation Training in Extended Reality with High-Fidelity Patient Simulator for Emergency Contexts

Abstract

This study aims to design and develop a collaborative simulation in extended reality (XR) environments that integrates a high-fidelity patient simulator to enhance emergency medical training, particularly in the context of Korea Advanced Life Support (KALS) education. In hospital settings, the ability to respond swiftly and effectively to cardiac arrest scenarios is essential, requiring structured team coordination, rapid decision-making, and effective communication. The team leader plays a central role in orchestrating the resuscitation process; however, existing training methods often fail to replicate the high-pressure, real-time decision-making requirements of actual emergency situations. To address these limitations, this study proposes an XR-based simulation that immerses learners in realistic emergency scenarios, allowing them to lead a virtual resuscitation team, issue commands, and implement life-saving interventions. By integrating a high-fidelity patient simulator with real-time interactive virtual team members, the training aims to enhance both technical and leadership skills. Additionally, the study will evaluate the effectiveness of XR-enhanced training in improving decision-making efficiency, team coordination, and preparedness for high-stakes medical emergencies. The broader implications of this research extend to scalability and adaptability, exploring how XR-based simulations can be expanded to other advanced life support training programs and integrated into global medical education frameworks.