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未来技术在检测技能衰退及改善操作表现方面的应用。

Applications of Future Technologies to Detect Skill Decay and Improve Procedural Performance.

作者信息

Linde Amber S, Miller Geoffrey T

机构信息

U.S. Medical Simulation and Information Sciences Research Program, 1054 Patchel Street, Fort Detrick, MD.

Telemedicine and Advanced Technology Research Center (TATRC), United States Army Medical Research and Materiel Command (USAMRMC), Fort Detrick, MD.

出版信息

Mil Med. 2019 Mar 1;184(Suppl 1):72-77. doi: 10.1093/milmed/usy385.

Abstract

Medical simulation training has progressed in its use of incorporating various technologies to provide quality training interfaces from novices to experts. The purpose of this paper is to explore modeling, simulation and visualization training technology interfaces to improve precision learning, rigorous, objective assessment, and performance improvement feedback for clinical procedural skill training and sustainment. Technologies to include augmented reality (AR), haptic technology and computer vision will be defined and clarified. It is believed that by exploring the combination of using AR, haptics and computer vision technologies it is possible to develop a fully immersive learning system that can automate mentoring while detecting and measuring gross and fine motor skills. Such a system can be used to predict or delay the onset of skills decay (SD) by capturing rigorous, objective measures, and human performance metrics that can provide feedback to individual performers for skills improvement in real time.

摘要

医学模拟训练在整合各种技术以提供从新手到专家的高质量训练界面方面取得了进展。本文的目的是探索建模、模拟和可视化训练技术界面,以改善临床程序技能训练与维持中的精准学习、严格客观评估以及性能提升反馈。将对包括增强现实(AR)、触觉技术和计算机视觉在内的技术进行定义和阐释。据信,通过探索AR、触觉和计算机视觉技术的结合,有可能开发出一个完全沉浸式的学习系统,该系统能够在检测和测量粗大和精细运动技能的同时实现自动指导。这样一个系统可用于通过获取严格、客观的测量数据以及人类绩效指标来预测或延缓技能衰退(SD)的发生,这些指标可为个体执行者提供实时的技能提升反馈。

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