Objective Assessment of Proficiency in Vaginal Cuff Closure Using Sensor Technology

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Faculty Advisor:

Karen Noblett, MD


Establish concurrent and construct validity of motion analysis in differentiating laparoscopic psychomotor skills when suturing laparoscopically on a validated vaginal cuff model.


Surgical simulation is most useful when it provides metrics that are accurate and meaningful to the learner. Motion analytics provides objective data that allows a comprehensive evaluation to assist with deconstructing complex tasks. This information may assist with formative feedback and deliberate practice.


Participants were divided based on number of laparoscopic vaginal cuff closures after hysterectomy. 15 Early Novices (0-20 procedures), 5 Advanced Novices (21-50 procedures), and 15 Experts (>51 procedures) in conventional laparoscopy and 24 Early Novices, 4 Advanced Novices, and 7 Experts in robotic-assisted laparoscopy were instructed to secure three stitches on a previously validated vaginal cuff model. A motion sensor was attached to each instrument, which subsequently recorded the hand movement of each participant. Each task was graded using the Global Operative Assessment of Laparoscopic Skills scale and a validated laparoscopic suturing checklist.


Comparison analysis indicated Experts in conventional laparoscopy operated with less hand movement (P<.01) and higher hand smoothness (P<.01) compared to Early Novices. Advanced Novices did not show any significant difference to Experts in terms of hand movement (P>.01) or smoothness (P>.01). In contrast, Experts in robotics did not show a difference between Early or Advanced Novices in either of these metrics.


Using a validated vaginal cuff model, hand movement and smoothness were found to correlate with experience for conventional laparoscopy. Robotic experience did not correlate with improved hand movement or smoothness on a conventional laparoscopic simulator.

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