New Highly Portable Simulator (SECMA) Based on Virtual Reality for Teaching Essential Skills in Minimally Invasive Surgeries

IF 1.7 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS International Journal of Online and Biomedical Engineering Pub Date : 2023-09-18 DOI:10.3991/ijoe.v19i13.40897
José Ignacio Guzmán, Mauricio Herrera, Camilo Rodríguez Beltrán
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Abstract

This study presents a new minimal access surgery training system, SECMA, and its constructive validation to determine its usefulness for training basic laparoscopic skills. SECMA is an affordable, highly portable, mobile virtual reality training tool for laparoscopic techniques that integrates the Oculus Quest with a mechanical interface for surgeon simulation of forceps using the hand controllers of these devices. It allows the execution of structured activities (supported by virtual scenarios simulating operating rooms developed in Unity), performance evaluation, and real-time data capture. Two experiments were carried out: 1) coordination; and 2) capture and transport, with a total of 21 individuals divided into two groups: a novice group (inexperienced) of 10 participants and an expert group (>100 endoscopic procedures) of 11 participants. Total task time score, right-hand speed, path length, and other metrics from several consecutive runs on the simulator were compared between experts and novices. Data automatically recorded by SECMA during the experiments were analyzed using hypothesis tests, linear regressions, analysis of variance, principal component analysis, and machine learning-supervised classifiers. In the experiments, the experts scored significantly better than the novices in all the parameters used. The tasks evaluated discriminated between the skills of experienced and novice surgeons, giving the first indication of construct validity for SECMA.
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基于虚拟现实的新型高便携模拟器(SECMA)用于微创手术基本技能的教学
本研究提出了一种新的微创手术培训系统SECMA,并对其进行了建设性的验证,以确定其在培训基本腹腔镜技能方面的有效性。SECMA是一款经济实惠,高度便携的移动虚拟现实腹腔镜技术培训工具,它将Oculus Quest与外科医生使用这些设备的手动控制器模拟镊子的机械界面集成在一起。它允许执行结构化活动(由Unity开发的模拟手术室的虚拟场景支持)、性能评估和实时数据捕获。进行了两个实验:1)协调;2)捕获和运输,共21人分为两组:新手组(没有经验)10人,专家组(>100内镜手术)11人。总任务时间得分,右手速度,路径长度,和其他指标从几个连续运行的模拟器在专家和新手之间进行比较。实验过程中由SECMA自动记录的数据使用假设检验、线性回归、方差分析、主成分分析和机器学习监督分类器进行分析。在实验中,在所有使用的参数中,专家的得分明显高于新手。评估的任务区分了经验丰富和新手外科医生的技能,给出了SECMA结构效度的第一个指示。
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来源期刊
CiteScore
4.00
自引率
46.20%
发文量
143
审稿时长
12 weeks
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