Virtual reality (VR) is increasingly being used to promote exercise among older adults. The data captured through VR may be useful indicator of the game user's experience as well as providing insight into functional ability of older adults. This paper presents classifiers to predict game user experience variables using VR data from community-dwelling older adults. Head-kinematic data of the VR headset was collected from 13 participants over a six-week period with three 20-minutes exergame sessions per week (e.g., 360 minutes per participant). Cognitive function was assessed using the Montreal Cognitive Assessment (MoCa) and multisensory response-time (RT). Game user experience was captured through perceived-levels of cybersickness, enjoyment, and exertion after each session. Data was used as references for discrete binary and ternary classification patterns. Combinations of kinematic features were used to train different classifiers: K-nearest-neighbors (KNN), linear discriminant analysis (LDA), support vector machines (SVM), and decision trees. Maximum classification accuracy of 70% was found for MoCa, 68% for perceived exertion, 60% for cybersickness, 59% for multisensory RT, and 53% for perceived enjoyment. Results suggest unobtrusive recording of head kinematics from VR headsets combined with machine learning classifiers could be used to predict cognition, exertion, and game user experience among older adults.

Virtual reality head mounted displays (VR-HMD) can immerse individuals into a variety of virtual environments while accounting for head orientation to update the virtual environment. VR-HMDs also allow users to explore environments while maintaining different body positions (e.g. sitting and laying down). How discrepancies between real world body position and the virtual environment impact the perception of virtual space or, additionally, how a visual upright with incongruent changes in head orientation affects space perception within VR has not been fully defined. In this study we sought to further understand how changes in head-on-body orientation (laying supine, laying prone, laying on left side and, being upright) while a steady visual virtual upright is maintained can affect the perception of distance. We used a new psychophysics perceptual matching based approach with two different probe configurations (“L” & “T” shape) to extract distance perception thresholds in the four previously mentioned positions at egocentric distances of 4, 5, and 6 virtual meters. Our results indicate that changes in observer orientation with respect to gravity impact the perception of distances with a virtual environment when it is maintained at a visual upright. Here we found significant differences between perceived distances in the upright condition compared to the prone and laying on left side positions. Additionally, we found that distance perception results were impacted by differences in probe configuration. Our results add to a body of work on how changes in head-on-body orientation can affect the perception of distance, while stressing that more research is still needed to fully understand how these changes with respect to gravity affect the perception of space within virtual environments.

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Games hold the potential to help many address health-related issues such as chronic stress. We investigated the use of biophilia, an affective response to nature grounded in the psychology literature, as indirect physiological input for biofeedback games. We designed and developed a non-violent exploration game, and conducted an empirical study that examined affective and physiological responses to gameplay in virtual nature and urban settings. Our results did not identify a difference in stress levels experienced by players between these two settings, but point to improved attention when playing in nature settings. We discuss implications of these findings, and discuss both difficulties in and potential future strategies for applying biophilia to the design of biofeedback games.