Demirel Doga, Yu Alexander, Halic Tansel, Sankaranarayanan Ganesh, Ryason Adam, Spindler David, Butler Kathryn L, Cao Caroline, Petrusa Emil, Molina Marcos, Jones Dan, De Suvranu, Demoya Marc, Jones Stephanie
Department of Computer Science, University of Central Arkansas.
Department of Mechanical, Aerospace and Nuclear Engineering, Rensselear Polytechnic Institute.
Stud Health Technol Inform. 2016;220:91-7.
This paper presents a simulation of Virtual Airway Skill Trainer (VAST) tasks. The simulated tasks are a part of two main airway management techniques; Endotracheal Intubation (ETI) and Cricothyroidotomy (CCT). ETI is a simple nonsurgical airway management technique, while CCT is the extreme surgical alternative to secure the airway of a patient. We developed identification of Mallampati class, finding the optimal angle for positioning pharyngeal/mouth axes tasks for ETI and identification of anatomical landmarks and incision tasks for CCT. Both ETI and CCT simulators were used to get physicians' feedback at Society for Education in Anesthesiology and Association for Surgical Education spring meetings. In this preliminary validation study, total 38 participants for ETI and 48 for CCT performed each simulation task and completed pre and post questionnaires. In this work, we present the details of the simulation for the tasks and also the analysis of the collected data from the validation study.
本文介绍了虚拟气道技能训练器(VAST)任务的模拟。模拟任务是两种主要气道管理技术的一部分;气管插管(ETI)和环甲膜切开术(CCT)。ETI是一种简单的非手术气道管理技术,而CCT是确保患者气道安全的极端手术替代方法。我们开发了马兰帕蒂分级识别、为ETI定位咽/口轴任务找到最佳角度以及为CCT识别解剖标志和切口任务。ETI和CCT模拟器都用于在麻醉学教育协会和外科学教育协会春季会议上获取医生的反馈。在这项初步验证研究中,共有38名参与ETI的参与者和48名参与CCT的参与者执行了每个模拟任务,并完成了术前和术后问卷。在这项工作中,我们展示了任务模拟的详细信息以及对验证研究收集数据的分析。