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. 2025 Mar 3;20(3):e0318660.
doi: 10.1371/journal.pone.0318660. eCollection 2025.

Quantitative metrics for evaluating surgical dexterity using virtual reality simulations

Affiliations

Quantitative metrics for evaluating surgical dexterity using virtual reality simulations

Mingyu Wu et al. PLoS One. .

Abstract

This study develops and evaluates quantitative metrics to assess surgical dexterity within virtual reality (VR) simulations to enhance surgical training and performance. By employing advanced VR technology, this research systematically investigates the influence of controlled experimental factors-posture, handedness, and visual magnification-on surgical performance. The impact of human factors such as surgical specialty, experience, and lifestyle factors like sleep and caffeine consumption on surgical dexterity is also analyzed. The findings reveal that seated posture, dominant hand usage, and enhanced visual magnification significantly improve surgical precision and efficiency. Contrary to common beliefs, lifestyle factors such as sleep duration and coffee consumption showed minimal impact on performance metrics. The study highlights the potential of VR simulations to provide a controlled, replicable, and safe environment for surgical training, emphasizing the importance of personalized training protocols that cater to individual surgeon's needs. The insights from this research advocate for integrating quantitative, objective metrics in surgical training programs to refine and accelerate dexterity acquisition, ultimately aiming to improve patient outcomes and surgical care.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. LAP Mentor high-fidelity virtual simulator.
Fig 2
Fig 2. Overall flowchart of research methodology.
Fig 3
Fig 3. Hardware implementation of the experimental setup.
Fig 4
Fig 4. Architecture of software deployment.
Fig 5
Fig 5. Summary of experimental setups with different controlled configurations.
Fig 6
Fig 6. Dynamic motion depicting the cursor moving from the starting point to the target point.
This phase assesses the surgeon’s ability to initiate and control movement toward a surgical target, which is critical for tasks that require reaching and positioning within a confined space.
Fig 7
Fig 7. Static motion showing the cursor reaching the target point and remaining steady for 3 seconds.
This phase evaluates the surgeon’s capacity for maintaining focus and stability, which is essential for performing precise surgical maneuvers.
Fig 8
Fig 8. Data grouping based on controlled experimental factors.
Fig 9
Fig 9. Composite figure illustrating the effects of visual magnification on surgical performance.
This figure compares 1x and 10x visual magnifications, showcasing their impact on motion path length, economy of movement, motion path accuracy, precision, and smoothness across various surgical tasks and target locations.
Fig 10
Fig 10. Composite figure illustrating the effects of visual magnification on surgical performance.
This figure compares 1x and 10x visual magnifications, demonstrating their impact on motion path length, economy of movement, and motion path precision across different target locations.
Fig 11
Fig 11. Comparison of surgical performance between dominant and non-dominant hands.
Fig 12
Fig 12. Comprehensive comparison of various performance metrics among different surgical specialties.
The metrics include motion path length, economy of movement, motion path accuracy, precision, and smoothness, highlighting significant differences observed particularly in oral and maxillofacial surgery.
Fig 13
Fig 13. Analysis of surgical performance across different years of experience, emphasizing depth-targeted tasks.
This figure integrates data on economy of movement and motion path length, showing enhanced performance in surgeons with 6 to 10 years of experience.
Fig 14
Fig 14. Effects of sleep duration on various performance metrics across different target locations, comparing groups with 4 to 6 hours and 6 to 8 hours of sleep.
Metrics include motion path length, economy of movement, accuracy, precision, smoothness, and endpoint metrics.
Fig 15
Fig 15. Effects of coffee consumption on surgical performance metrics, aggregating data across various coffee consumption levels and target locations.
Differences in performance metrics such as motion path length, economy of movement, and accuracy are highlighted among groups consuming different amounts of coffee daily.
Fig 16
Fig 16. Comparative analysis of the impact of video game exposure on surgical performance, showing metrics such as motion path length, economy of movement, accuracy, precision, smoothness, and endpoint metrics across different target locations for surgeons with and without video game experience.

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