Siu Ka-Chun, Best Bradley J, Kim Jong Wook, Oleynikov Dmitry, Ritter Frank E
University of Nebraska Medical Center, 984220 Nebraska Medical Center, Omaha, NE 68198.
Adaptive Cognitive Systems, 909 Harris Avenue, Suite 202D, Bellingham, WA 98225.
Mil Med. 2016 May;181(5 Suppl):214-20. doi: 10.7205/MILMED-D-15-00164.
The Department of Defense has pursued the integration of virtual reality simulation into medical training and applications to fulfill the need to train 100,000 military health care personnel annually. Medical personnel transitions, both when entering an operational area and returning to the civilian theater, are characterized by the need to rapidly reacquire skills that are essential but have decayed through disuse or infrequent use. Improved efficiency in reacquiring such skills is critical to avoid the likelihood of mistakes that may result in mortality and morbidity. We focus here on a study testing a theory of how the skills required for minimally invasive surgery for military surgeons are learned and retained. Our adaptive virtual reality surgical training system will incorporate an intelligent mechanism for tracking performance that will recognize skill deficiencies and generate an optimal adaptive training schedule. Our design is modeling skill acquisition based on a skill retention theory. The complexity of appropriate training tasks is adjusted according to the level of retention and/or surgical experience. Based on preliminary work, our system will improve the capability to interactively assess the level of skills learning and decay, optimizes skill relearning across levels of surgical experience, and positively impact skill maintenance. Our system could eventually reduce mortality and morbidity by providing trainees with the reexperience they need to help make a transition between operating theaters. This article reports some data that will support adaptive tutoring of minimally invasive surgery and similar surgical skills.
美国国防部一直在寻求将虚拟现实模拟技术融入医学培训和应用中,以满足每年培训10万名军事医护人员的需求。医疗人员在进入作战区域和返回民用战区时的角色转换,其特点是需要迅速重新掌握那些至关重要但因长期不用或很少使用而生疏的技能。提高重新掌握这些技能的效率对于避免可能导致死亡和发病的错误至关重要。我们在此重点关注一项研究,该研究测试了一种关于军事外科医生进行微创手术所需技能是如何学习和保持的理论。我们的自适应虚拟现实手术训练系统将纳入一种智能机制来跟踪表现,该机制将识别技能缺陷并生成最佳的自适应训练计划。我们的设计基于技能保持理论对技能习得进行建模。适当训练任务的复杂性会根据保持水平和/或手术经验进行调整。基于初步工作,我们的系统将提高交互式评估技能学习和衰退水平的能力,优化不同手术经验水平的技能重新学习,并对技能维持产生积极影响。我们的系统最终可能通过为学员提供他们在不同手术室之间转换所需的重新体验来降低死亡率和发病率。本文报告了一些将支持微创手术和类似手术技能的自适应辅导的数据。