I Need to Step Back from It! Modeling Backward Movement from Multimodal Sensors in Virtual Reality

Abstract

A user’s movement is one of the most important properties that pertain to user experience in a virtual reality (VR) environment. However, little research has focused on examining backward movements. Inappropriate support of such movements could lead to dizziness and disengagement in a VR program. In this paper, we investigate the possibility of detecting forward and backward movements from three different positions of the body (i.e., head, waist, and feet) by conducting a user study. Our machine-learning model yields the detection of forward and backward movements up to 93% accuracy and shows slightly varying performances by the participants. We detail the analysis of our model through the lenses of body position, integration, and sampling rate.