Enhancing Surgical Robotic Skills Through Performance‐Guided Training: A Swimmer’s Approach for Defining Key Metrics

摘要

Background: In swimming, a combination of strength, endurance, and targeted skill training significantly enhances performance, particularly by balancing aerobic and anaerobic conditioning. Similarly, in surgery, improving motor control and stamina during lengthy operations, particularly for precise movements like suturing or tissue manipulation, is essential. This literature review aims to explore the parallels between the training paradigms of elite swimming and robotic-assisted surgical practice, focusing on skill acquisition, training methodologies, and performance-guided feedback systems. The hypothesis suggests a significant link between these training principles, offering opportunities to optimize surgeon training, particularly in robotic-assisted surgery. Database: A systematic review was conducted following PRISMA guidelines. A thorough examination of existing literature in both elite swimming and robotic-assisted surgery training identified key elements of skill development, feedback mechanisms, and structured progression. Sources included peer-reviewed studies on swimming techniques, cognitive training in surgery, and simulation-based training programs that emphasize performance-driven improvements. Conclusion: The review identified significant parallels between swimming and robotic-assisted surgery training, with both fields emphasizing structured, feedback-driven approaches to enhance precision and skill. Techniques such as video analysis in swimming and real-time digital feedback in surgery were found to be effective in improving outcomes. Simulation-based training also plays a crucial role in refining skills and promoting adaptability in both disciplines. Applying elite swimming methodologies, particularly those centered on feedback, precision, and structured progression, could help develop key metrics to enhance surgical training programs, in robotic-assisted surgery. Future research could further optimize surgeon training, potentially leading to improved performance and better patient outcomes in robotic procedures.