Neural insights on expert surgeons' mental workload during live robotic surgeries

Area of Science:

• Neurosurgery
• Surgical Technology
• Cognitive Neuroscience

Background:

• Robotic surgery offers benefits but increases surgeon mental workload.
• Current workload assessments are often post-procedure and lack dynamic insight.
• Objective intraoperative measurement of mental workload is needed.

Purpose of the Study:

• To investigate electroencephalogram (EEG) neural activity for measuring intraoperative mental workload in expert surgeons.
• To correlate EEG patterns with perceived mental workload during robotic-assisted urological procedures.

Main Methods:

• Collected EEG data from five surgeons during 13 robotic-assisted urological surgeries.
• Analyzed EEG signals across three surgical phases: before, critical, and after.
• Used a linear mixed effects model to assess the relationship between surgical phases, subjective workload ratings, and EEG spectral band power.

Main Results:

• Relative theta band power in the frontal region was significantly higher during critical surgical phases (p < 0.05).
• Increased subjective mental workload ratings correlated with higher relative frontal theta band power (p < 0.001).
• Decreased relative parietal alpha band power was observed as subjective workload ratings increased across all phases.

Conclusions:

• EEG signals can effectively differentiate intraoperative mental workload in robotic surgery.
• This neurophysiological monitoring has potential applications in predicting surgical complexity and enhancing surgical education.
• Objective EEG-based workload assessment provides a dynamic alternative to subjective, post-operative measures.