Sensitivity to Redirected Walking Considering Gaze, Posture, and Luminance

TL;DR

This study investigates how redirected walking (RDW) rotation gains relate to users' gaze and posture in VR and whether display luminance (photopic vs. mesopic) affects RDW detection thresholds. A psychophysical rotation-discrimination task with nine gain values, spanning a virtual rotation of $90^{\circ}$ (±$5^{\circ}$), was conducted in two luminance blocks while recording gaze and posture data; a multilevel (hierarchical) analysis examined effects of gain, trial duration, trial number, and gender. The main findings show that physiological signals (gaze velocity, postural sway, blinks, and saccades) are significantly positively correlated with RDW gain and exposure, while luminance did not significantly alter detection thresholds. These results support the potential for real-time, noninvasive physiological monitoring to adapt RDW gains to individual tolerance, enhancing practicality and safety of RDW in a wide range of VR applications, including HDR displays and varied lighting environments.

Abstract

We study the correlations between redirected walking (RDW) rotation gains and patterns in users' posture and gaze data during locomotion in virtual reality (VR). To do this, we conducted a psychophysical experiment to measure users' sensitivity to RDW rotation gains and collect gaze and posture data during the experiment. Using multilevel modeling, we studied how different factors of the VR system and user affected their physiological signals. In particular, we studied the effects of redirection gain, trial duration, trial number (i.e., time spent in VR), and participant gender on postural sway, gaze velocity (a proxy for gaze stability), and saccade and blink rate. Our results showed that, in general, physiological signals were significantly positively correlated with the strength of redirection gain, the duration of trials, and the trial number. Gaze velocity was negatively correlated with trial duration. Additionally, we measured users' sensitivity to rotation gains in well-lit (photopic) and dimly-lit (mesopic) virtual lighting conditions. Results showed that there were no significant differences in RDW detection thresholds between the photopic and mesopic luminance conditions.

Figures (6)

• Figure 1: Screenshots of the virtual office environment used in our experiment (during the photopic condition). Ambient office sounds were played to help mitigate the viability of using sounds from the physical environment as a cue for the participant's orientation in the physical space. (A) The view of the environment that participants saw at the beginning of each trial. The white arrow indicated to the user which direction they should rotate, and this arrow disappeared after they rotated $5^\circ$ from the starting position in the direction of the arrow. (B) An example view of the environment at the end of a trial. When the user rotated $90^\circ$ in the virtual environment ($\pm 5^\circ$), a beep tone was played that indicated that the user should stop rotating and maintain their current orientation in the environment. After maintaining this orientation for 1 second, a green check mark appeared to indicate that they successfully completed the trial.
• Figure 2: Psychometric curves fit to participants' pooled response data for the photopic (yellow) and mesopic (blue) conditions. The graph shows the average probability of responding "greater" to the post-trial question "Was the virtual movement smaller or greater than the physical movement?". The yellow- and blue-shaded regions indicate the estimated range of rotation gains that are usually imperceptible to users (i.e., the 25% and 75% detection thresholds). Error bars for each data point denote the standard error. The pooled detection thresholds for photopic and mesopic conditions were similar to values found in prior work that used photopic stimuli, and there were no significant differences between the two conditions. The detection threshold gains shown here are not exactly the same as the average values shown in \ref{['tab:thresholds']} since we computed the curves in this plot by fitting a psychometric curve to the pooled participant responses, while \ref{['tab:thresholds']} computes the average of the curves fit to individual participants' responses for each conditions.
• Figure 3: A scatter plot of users' SS scores after the light (photopic) and dark (mesopic) blocks of our experiment. In general, participants exhibited SS levels that are typical of RDW detection threshold experiments. The data belonging to the outlier male participant with the highest SS scores did not show any anomalous patterns, so their data are included in our analyses.
• Figure 4: Examples of one participant's posture data for two different trials (each row corresponds to one trial). The left column shows the participant's head position projected onto the ground plane (black curve), with the centroid of their positions at the origin (red dot). For each trajectory point sampled, we compute a proxy for postural sway as the distance between the centroid and the sampled head position (i.e., the distance from each point to the origin). The right column shows the participant's postural sway (purple curve) and total amount rotated in the physical environment (orange curve) across the duration of the trial. The points along the trajectory curves and postural sway curves are colored according to the time in the trial (purple indicates the beginning of the trial, yellow indicates the end of the trial). These plots show that as the gain increases, participants' postural sway also increases---a correlation which was statistically significant (\ref{['subsec:postural_stabililty']}).
• Figure 5: An example of one participant's horizontal eye position (red curve, in UV coordinates of the rendered image) during one trial. Green indicate saccades (gaze velocity above $30^\circ$), which are also identifiable as a very steep slope in the red curve, denoting the eye's horizontal position. The data help to confirm that our participants' gaze behavior was free of abnormalities since this plot shows that gaze behavior was characterized by typical nystagmus responses that are expected in healthy observers during head rotation abadi2002mechanisms.