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

Abstract

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.