Objective evaluation of laparoscopic surgical skills in wet lab training based on motion analysis and machine learning.

ABSTRACT:

Background

Our aim was to build a skill assessment system, providing objective feedback to trainees based on the motion metrics of laparoscopic surgical instruments.

Methods

Participants performed tissue dissection around the aorta (tissue dissection task) and renal parenchymal closure (parenchymal-suturing task), using swine organs in a box trainer under a motion capture (Mocap) system. Two experts assessed the recorded movies, according to the formula of global operative assessment of laparoscopic skills (GOALS: score range, 5-25), and the mean scores were utilized as objective variables in the regression analyses. The correlations between mean GOALS scores and Mocap metrics were evaluated, and potential Mocap metrics with a Spearman's rank correlation coefficient value ex

SUBMITTER: Ebina K 

PROVIDER: S-EPMC9399206 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature