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Virtual Reality vs Dry Laboratory Models: Comparing Automated Performance Metrics and Cognitive Workload During
Andrew Cowan1, Jian Chen1, Samuel Mingo1
1Center for Robotic Simulation and Education, Catherine and Joseph Aresty Department of Urology, USC Institute of Urology, University of Southern California, Los Angeles, California, USA.
Journal of Endourology
|July 8, 2021
Summary
This study found that most robotic surgery skills trained in virtual reality (VR) transfer to dry laboratory (DL) simulations. However, dry lab metrics better distinguish surgical expertise than VR metrics.
Area of Science:
- Robotic Surgery
- Surgical Education
- Medical Simulation
Background:
- Assessing surgical skill transferability between virtual reality (VR) and dry laboratory (DL) robotic surgery training environments is crucial for effective surgical education.
- Understanding how performance metrics in VR correlate with real-world surgical performance in DL is essential for validating simulation-based training.
Purpose of the Study:
- To compare surgical performance metrics during vesico-urethral anastomosis (VUA) tasks in VR and DL robotic training environments.
- To investigate the transferability of surgical skills and the ability of each environment to distinguish between expert and trainee surgeons.
- To determine if performance in VR correlates with performance in live robotic surgery (DL).
Main Methods:
- Experts and trainees performed VUA tasks in both VR and DL robotic environments using a da Vinci console.
- Computer-generated metrics (kinematic, tissue, biometrics) and pupillary data (Index of Cognitive Activity [ICA]) were collected in both settings.
- Statistical analyses (Pearson correlation, Mann-Whitney, independent t-tests) were used to compare performance and cognitive workload between environments and expertise levels.
Main Results:
- A significant positive correlation was observed between most comparable metrics (8/9) across VR and DL environments, indicating skill transferability.
- Dry laboratory (DL) automated performance metrics (APMs) were more effective in distinguishing surgical expertise (14/22 metrics) compared to VR metrics (5/22 metrics).
- Trainees exhibited higher cognitive workload (ICA) than experts in both VR and DL settings.
Conclusions:
- Performance metrics demonstrate moderate to strong correlations between VR and DL, supporting skill transferability across these robotic surgery training platforms.
- Dry laboratory (DL) tasks provide superior metrics for differentiating surgical expertise compared to virtual reality (VR) simulations.
- Cognitive workload is higher in trainees than experts, irrespective of the training environment.
