Literature DB >> 23295136

da Vinci skills simulator for assessing learning curve and criterion-based training of robotic basic skills.

Willem M Brinkman1, Jan-Maarten Luursema, Bas Kengen, Barbara M A Schout, J Alfred Witjes, Ruud L Bekkers.   

Abstract

OBJECTIVE: To answer 2 research questions: what are the learning curve patterns of novices on the da Vinci skills simulator parameters and what parameters are appropriate for criterion-based robotic training.
MATERIALS AND METHODS: A total of 17 novices completed 2 simulator sessions within 3 days. Each training session consisted of a warming-up exercise, followed by 5 repetitions of the "ring and rail II" task. Expert participants (n = 3) performed a warming-up exercise and 3 repetitions of the "ring and rail II" task on 1 day. We analyzed all 9 parameters of the simulator.
RESULTS: Significant learning occurred on 5 parameters: overall score, time to complete, instrument collision, instruments out of view, and critical errors within 1-10 repetitions (P <.05). Economy of motion and excessive instrument force only showed improvement within the first 5 repetitions. No significant learning on the parameter drops and master workspace range was found. Using the expert overall performance score (n = 3) as a criterion (overall score 90%), 9 of 17 novice participants met the criterion within 10 repetitions.
CONCLUSION: Most parameters showed that basic robotic skills are learned relatively quickly using the da Vinci skills simulator, but that 10 repetitions were not sufficient for most novices to reach an expert level. Some parameters seemed inappropriate for expert-based criterion training because either no learning occurred or the novice performance was equal to expert performance.
Copyright © 2013 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2013        PMID: 23295136     DOI: 10.1016/j.urology.2012.10.020

Source DB:  PubMed          Journal:  Urology        ISSN: 0090-4295            Impact factor:   2.649


  14 in total

1.  Robotic surgery, skills and simulation: a technical sport.

Authors:  S S Goonewardene; D Cahill
Journal:  J Robot Surg       Date:  2015-11-14

Review 2.  Current state of virtual reality simulation in robotic surgery training: a review.

Authors:  Justin D Bric; Derek C Lumbard; Matthew J Frelich; Jon C Gould
Journal:  Surg Endosc       Date:  2015-08-25       Impact factor: 4.584

3.  Can we become better robot surgeons through simulator practice?

Authors:  Ankit Patel; Meghna Patel; Nathaniel Lytle; Juan P Toro; Rachel L Medbery; Sheryl Bluestein; Sebastian D Perez; John F Sweeney; S Scott Davis; Edward Lin
Journal:  Surg Endosc       Date:  2014-03       Impact factor: 4.584

4.  Can a virtual reality surgical simulation training provide a self-driven and mentor-free skills learning? Investigation of the practical influence of the performance metrics from the virtual reality robotic surgery simulator on the skill learning and associated cognitive workloads.

Authors:  Gyusung I Lee; Mija R Lee
Journal:  Surg Endosc       Date:  2017-06-20       Impact factor: 4.584

Review 5.  Evolution and literature review of robotic general surgery resident training 2002-2018.

Authors:  David L Crawford; Anthony Michael Dwyer
Journal:  Updates Surg       Date:  2018-07-27

Review 6.  The effect of warm-up on surgical performance: a systematic review.

Authors:  Gamal Abdalla; Erin Moran-Atkin; Grace Chen; Michael A Schweitzer; Thomas H Magnuson; Kimberley E Steele
Journal:  Surg Endosc       Date:  2014-08-23       Impact factor: 4.584

7.  A methodological, task-based approach to Procedure-Specific Simulations training.

Authors:  Yaki Setty; Oren Salzman
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-07-04       Impact factor: 2.924

8.  Distribution of innate ability for surgery amongst medical students assessed by an advanced virtual reality surgical simulator.

Authors:  Andrea Moglia; Vincenzo Ferrari; Luca Morelli; Franca Melfi; Mauro Ferrari; Franco Mosca; Alfred Cuschieri
Journal:  Surg Endosc       Date:  2014-01-18       Impact factor: 4.584

9.  Virtual reality surgical simulators- a prerequisite for robotic surgery.

Authors:  Anupama Rajanbabu; Laura Drudi; Susie Lau; Joshua Z Press; Walter H Gotlieb
Journal:  Indian J Surg Oncol       Date:  2014-05-30

10.  Sensor-based indicators of performance changes between sessions during robotic surgery training.

Authors:  Chuhao Wu; Jackie Cha; Jay Sulek; Chandru P Sundaram; Juan Wachs; Robert W Proctor; Denny Yu
Journal:  Appl Ergon       Date:  2020-09-19       Impact factor: 3.661

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.