Adaptive virtual reality

Virtual reality (VR) technology can be used to induce emotional states during academic studies and immersive experiences. This application of VR can be extended through an adaptive interactive mechanism (AIM), which alters aspects of the virtual environment (VE) in real-time to create personalized experiences calibrated to the individual user. Adaptive VR functions on the basis of a closed-loop design, where behavior, psychophysiology, or neurophysiology is monitored to create a real-time model of the user. This quantification is used to infer the emotional state of the individual user and trigger adaptive changes within the VE during run time. This chapter will describe the rationale underpinning the concept of adaptive VR, how distinct groups of AIMs can be organized into a framework and delineates the closed-loop design underpinning this concept. It is argued that adaptive VR can increase the potency of emotional experiences by allowing the system to model individual variation as users interact within a specific VE. A VR study is described that demonstrates how individual differences can be predicted based on an interaction history in a specific context in VR. Participants were monitored in a VE designed to induce threat using a virtual height scenario. Data were used to predict individual traits such as age, gender, neuroticism, and openness. The same data were utilized to predict the likelihood of subsequent behavioral outcomes. The study demonstrates the potential of implicit monitoring within a VE, which illustrates how adaptive VR can create experiences tailored to the individual.