The human side of robotic surgery: Tracking surgeons' stress in the operating room

Robot-assisted surgery (RAS) is a highly advanced medical tool that allows surgeons to perform complex procedures through small incisions, reducing pain and recovery time for patients. However, these operations still rely heavily on the expertise and focus of human surgeons, who must remain intensely concentrated for extended periods.

As RAS is adopted more widely across the globe, understanding the demands placed on surgeons has become increasingly important. While existing research acknowledges that surgeons experience varying levels of stress during operations, precise data on how this stress fluctuates in real-time is limited. Traditionally, researchers have used simulated surgeries or post-operative questionnaires, which fail to capture the rapid physiological changes occurring during actual procedures.

Professor Yoshihiro Shimomura and his team from Chiba University in Japan aimed to bridge this gap by monitoring seven experienced urologists during live robot-assisted surgeries. They recorded multiple physiological signals simultaneously using lightweight sensors: electroencephalography to measure brain activity, surface electromyography for muscle activity in the shoulder and neck, and electrocardiography to track heart function.

After each procedure, surgeons watched a playback of their console view and marked instances where they perceived their stress level to change, rating it on a scale of 0 to 9. By analyzing 151 of these stress-rated moments across the seven surgeons, the researchers discovered that four specific physiological signals consistently correlated with the surgeons' self-reported stress levels.

These included heightened brain activity linked to mental arousal, increased muscle tension in the upper shoulder, elevated heart rate, and a decrease in the natural variability between heartbeats. The researchers note that this multimodal physiological monitoring approach offers valuable insights into the challenges faced by surgeons, enabling the identification of high-demand moments during surgical procedures.

This method, when combined with surgeon-reported stress annotations, can inform ergonomic design, communication routines, workload distribution, and training stages within the robotic surgery work system. The findings suggest that understanding and managing surgeons' stress through real-time physiological monitoring could enhance surgical performance, improve working environments, and support stress management for novice surgeons utilizing double-console systems.