Analysis of Energy-Based Metrics for Laparoscopic Skills Assessment

IEEE Trans Biomed Eng. 2018 Jul;65(7):1532-1542. doi: 10.1109/TBME.2017.2706499. Epub 2017 May 19.

Abstract

Objective: The complexity of minimally invasive surgery (MIS) requires that trainees practice MIS skills in numerous training sessions. The goal of these training sessions is to learn how to move the instruments smoothly without damaging the surrounding tissue and achieving operative tasks with accuracy. In order to enhance the efficiency of these training sessions, the proficiency of the trainees should be assessed using an objective assessment method. Several performance metrics have been proposed and analyzed for MIS tasks. The differentiation of various levels of expertise is limited without the presence of an external evaluator.

Methods: In this study, novel objective performance metrics are proposed based on mechanical energy expenditure and work. The three components of these metrics are potential energy, kinetic energy, and work. These components are optimally combined through both one-step and two-step methods. Evaluation of these metrics is accomplished for suturing and knot-tying tasks based on the performance of 30 subjects across four levels of experience.

Results: The results of this study show that the one-step combined metric provides 47 and 60 accuracy in determining the level of expertise of subjects for the suturing and knot-tying tasks, respectively. The two-step combined metric provided 67 accuracy for both of the tasks studied.

Conclusion: The results indicate that energy expenditure is a useful metric for developing objective and efficient assessment methods.

Significance: These metrics can be used to evaluate and determine the proficiency levels of trainees, provide feedback and, consequently, enhance surgical simulators.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Clinical Competence
  • Educational Measurement / methods*
  • Humans
  • Laparoscopy / education*
  • Laparoscopy / statistics & numerical data*
  • Suture Techniques
  • Task Performance and Analysis