A System for Surgeon Fatigue Monitoring in Robotic Surgery

Abstract

Surgeon fatigue during robotic surgery is an often-overlooked factor contributing to patient harm. This study presents the design, development, and testing of a real-time fatigue monitoring system aimed at enhancing safety in robotic surgery using the da Vinci surgical system. The system monitors critical fatigue indicators, including instrument collisions, blink rate, and workspace utilization, delivering immediate feedback to surgeons to mitigate fatigue-induced errors. The system was verified with simulated fatigue scenarios, such as reduced blink rates, abrupt tool movements, and inefficient utilization of the surgical workspace. The verification testing showed that the system detected fatigue-related indicators and provided timely alerts. This research underscores the potential of integrating advanced real-time monitoring technologies into robotic-assisted surgical practice to improve safety and efficiency. By identifying early signs of fatigue, the system facilitates immediate interventions, potentially preventing surgical errors. Additionally, the data collected can inform proactive future scheduling strategies to address surgeon fatigue. While the system demonstrated promising performance in simulated environments, further validation through subject studies and clinical trials is essential to establish its efficacy in real-world surgical settings.