Description

The integration of digital twin systems with surgical robotics represents a promising frontier in surgical innovation. This half-day workshop introduces the concept of cognitive digital twins (CDT) in both open and robotic/minimally invasive surgery, exploring how real-time modeling of surgeons’ and team members’ cognitive processes and workload may lead to enhancement of surgical performance, training, and safety. Furthermore, by combining advances in cognitive modeling with advanced surgical robotics, CDTs offer the potential to create adaptive and increasingly autonomous surgical systems that respond to surgeons’ cognitive load, decision-making patterns, and situational awareness.
The workshop will address current digital twin applications in healthcare, particularly focusing on their evolution from manufacturing to clinical environments, and explore the unique challenges and opportunities in developing cognitive digital twins for robotic surgery, including data integration, real-time cognitive monitoring, and adaptive interface design. Practical implementations, showcasing how CDTs can capture and analyze surgeon decision-making patterns while providing responsive support during procedures will be demonstrated.
Interactive demonstrations will allow participants to engage with prototype systems, experiencing firsthand how cognitive digital twins can enhance surgical training and performance optimization. These demonstrations will highlight the integration of digital biomarkers, cognitive load monitoring, and adaptive interfaces in surgical applications.
The workshop concludes with an expert panel discussion addressing critical questions about implementation challenges, ethical considerations, and future directions. This discussion will emphasize the practical steps needed to advance cognitive digital twins from theoretical concepts to clinical applications in robotic surgery.
This half-day workshop brings together surgeons, researchers, human factors experts, cognitive scientists, medical device engineers, and computer scientists to explore the transformative potential of cognitive digital twins in surgery. Through collaborative discussion and hands-on experience, participants will gain practical insights into implementing this technology while contributing to its future development.

Programme

The programme will be published in May.

Learning Outcomes

• Understand the fundamental principles of cognitive digital twins and their specific applications in robotic surgery, including the theoretical framework for integrating cognitive modeling with surgical systems.
• Evaluate the current capabilities and limitations of cognitive digital twin technology in surgical applications, enabling informed decisions about potential implementations in research or clinical settings. This includes assessing various approaches to cognitive monitoring and adaptive system design.
• Apply key concepts in cognitive modeling to surgical robotics applications, including methods for capturing surgeon decision-making patterns, analyzing cognitive load, and implementing adaptive interfaces.
• Participants will gain hands-on experience with prototype systems demonstrating these principles.
• Identify critical challenges in implementing cognitive digital twins in surgical environments and develop strategies for addressing these challenges through appropriate technical and methodological approaches. This includes considerations of data integration, real-time processing, and clinical validation requirements.
• Contribute to the emerging field of cognitive digital twins in surgery through informed participation in research discussions and collaborative initiatives, building on the workshop’s theoretical and practical foundations.