Abstract: PD46-01
Sources of Funding: Roswell Park Alliance Foundation

Introduction

Although robot-assisted surgery (RAS) provides many advantages in terms of ergonomics, visualization, and perioperative outcomes, it adds complexity to the surgical environment, due to its remoteness. Cognition-based trust is related to performance-relevant understandings such as competence, responsibility, reliability, integrity, and dependability. We sought to develop an objective method for evaluation of cognition-based trust during RAS.

Methods

We examined EEG data from a mentor who observed 116 Urethro-vesical anastomoses (UVAs) and 98 pelvic lymph node dissections (PLNDs) performed by 3 trainees. The mentor assessed trainee performance using NASA-TLX questionnaires at the end of each step. Procedures were classified as Trustworthy (mentor satisfied) or Concerning (mentor not satisfied) based on the performance score given by the mentor. We tested 68 features extracted from EEG data and applied Kernel Target Alignment (KTA) method to find the most discriminative features. The outcome of the classification was evaluated using the accuracy, sensitivity and specificity of these objective features in their ability to distinguish between trustworthy and concerning procedures.

Results

Of all features tested, we found that the five most predictive features were Stress, mental workload (MW), Frustration, Surprise and Modularity. These features were significantly different between Trustworthy and Concerning performances, showing higher frustration, stress, MW, surprise and lower modularity while mentoring concerning as opposed to trustworthy performances.

Conclusions

Cognition-based Trust can be objectively evaluated using EEG features. This is the first reported study to objectively evaluate trust during RAS by featuring cognitive and brain functioning features.

Funding

Roswell Park Alliance Foundation