Detecting Mental Workload in Surgical Teams Using a Wearable Single-Channel Electroencephalographic Device

Objective: To assess the sensitivity of an electroencephalographic (EEG)-based index, the prefrontal beta power, to quantify the mental workload in surgeons in real scenarios. Such EEG-based index might offer unique and unbiased measures of overload, a crucial factor when designing learning and training surgical programs.

Design: The experiment followed a 2 × 2 × 2 within subjects design with 3 factors: (1) Surgical Role during the surgery (primary surgeon vs. assistant surgeon), (2) the Surgical Procedure (laparo-endoscopic single-site [LESS] surgery vs. multiport laparoscopic surgery [MPS]), and (3) the Suturing Techniques (interrupted vs. continuous suture).

Setting: The study was carried out at the Advanced Multi-Purpose Simulation and Technological Innovation Complex situated at IAVANTE (Granada, Spain).

Methods: Four surgical teams (primary surgeon and assistant surgeon, experts in MPS) performed 8 surgical exercises on porcine models, under different task complexities. They performed 2 suturing techniques (continuous and interrupted), employing a low complex procedure (MPS) and a high complex procedure (LESS). Surgeons acted as the primary surgeon during half of the exercises, and, as the assistant surgeon, during the rest of them. Simultaneously, we monitored EEG prefrontal EEG beta power spectra of both surgeons, using 2 synchronized wearable EEG devices. We also collected performance and subjective data.

Results: Surgical complexity modulated prefrontal beta power. LESS surgery caused significant higher prefrontal beta power for both suturing techniques for both surgical roles which indicates higher demands than MPS. Perceived task complexity, overall surgical evaluation, and laparoscopic execution time confirmed EEG-based results. Finally, subjective ratings of surgical complexity differentiated between surgical roles within the same exercise, even when prefrontal beta power did not.

Conclusions: To detect mental overload when surgeons are engaged with complex surgeries, real or simulated, is still guesswork. EEG-based indices have great potential as objective and nonintrusive measures to assess mental overload in surgeons. Furthermore, EEG-based indices might play a relevant role in monitoring surgeons and residents' cognitive state during their training.