Designing a Physiological Loop for the Adaptation of Virtual Human Characters in a Social VR Scenario

Abstract

Social virtual reality is getting mainstream not only for entertainment purposes but also for productivity and education. This makes the design of social VR scenarios functional to support the operator's performance. We present a physiologically-adaptive system that optimizes for visual complexity in a dual-task scenario based on electrodermal activity. Specifically, we propose a system that adapts the amount of non-player characters while jointly performing an N-Back task (primary) and visual detection task (secondary). Our preliminary results show that when optimizing the complexity of the secondary task, users report an improved user experience.