Measuring Stress in an Augmented Training Environment: Approaches and Applications

Abstract

Augmented reality AR and virtual reality VR training systems provide an opportunity to place learners in high stress conditions that are impossible in real life due to safety risks or the associated costs. Using physiological classifiers it is possible to continually measure the stress levels of learners within AR and VR training environments to adapt training based on their responses. This paper reviews stress measurement approaches, outlines an adaptive stress training model that can be applied to augment training and describes key characteristics and future research that is critical to realizing adaptive VR and AR training platforms that take into account learner stress levels.