A threat to a virtual hand elicits motor cortex activation.

We report an experiment where participants observed an attack on their virtual body as experienced in an immersive virtual reality (IVR) system. Participants sat by a table with their right hand resting upon it. In IVR, they saw a virtual table that was registered with the real one, and they had a virtual body that substituted their real body seen from a first person perspective. The virtual right hand was collocated with their real right hand. Event-related brain potentials were recorded in two conditions, one where the participant's virtual hand was attacked with a knife and a control condition where the knife only struck the virtual table. Significantly greater P450 potentials were obtained in the attack condition confirming our expectations that participants had a strong illusion of the virtual hand being their own, which was also strongly supported by questionnaire responses. Higher levels of subjective virtual hand ownership correlated with larger P450 amplitudes. Mu-rhythm event-related desynchronization in the motor cortex and readiness potential (C3-C4) negativity were clearly observed when the virtual hand was threatened-as would be expected, if the real hand was threatened and the participant tried to avoid harm. Our results support the idea that event-related potentials may provide a promising non-subjective measure of virtual embodiment. They also support previous experiments on pain observation and are placed into context of similar experiments and studies of body perception and body ownership within cognitive neuroscience.

Putting yourself in the skin of a black avatar reduces implicit racial bias.

Although it has been shown that immersive virtual reality (IVR) can be used to induce illusions of ownership over a virtual body (VB), information on whether this changes implicit interpersonal attitudes is meager. Here we demonstrate that embodiment of light-skinned participants in a dark-skinned VB significantly reduced implicit racial bias against dark-skinned people, in contrast to embodiment in light-skinned, purple-skinned or with no VB. 60 females participated in this between-groups experiment, with a VB substituting their own, with full-body visuomotor synchrony, reflected also in a virtual mirror. A racial Implicit Association Test (IAT) was administered at least three days prior to the experiment, and immediately after the IVR exposure. The change from pre- to post-experience IAT scores suggests that the dark-skinned embodied condition decreased implicit racial bias more than the other conditions. Thus, embodiment may change negative interpersonal attitudes and thus represent a powerful tool for exploring such fundamental psychological and societal phenomena.

Measuring Embodiment: Movement Complexity and the Impact of Personal Characteristics.

A user's personal experiences and characteristics may impact the strength of an embodiment illusion and affect resulting behavioral changes in unknown ways. This paper presents a novel re-analysis of two fully-immersive embodiment user-studies (n=189 and n=99) using structural equation modeling, to test the effects of personal characteristics on subjective embodiment. Results demonstrate that individual characteristics (gender, participation in science, technology, engineering or math - Experiment 1, age, video gaming experience - Experiment 2) predicted differing self-reported experiences of embodiment Results also indicate that increased self-reported embodiment predicts environmental response, in this case faster and more accurate responses within the virtual environment. Importantly, head-tracking data is shown to be an effective objective measure for predicting embodiment, without requiring researchers to utilize additional equipment.

Effects of Transparency on Perceived Humanness: Implications for Rendering Skin Tones Using Optical See-Through Displays.

Current optical see-through displays in the field of augmented reality are limited in their ability to display colors with low lightness in the hue, saturation, lightness (HSL) color space, causing such colors to appear transparent. This hardware limitation may add unintended bias into scenarios with virtual humans. Humans have varying skin tones including HSL colors with low lightness. When virtual humans are displayed with optical see-through devices, people with low lightness skin tones may be displayed semi-transparently while those with high lightness skin tones will be displayed more opaquely. For example, a Black avatar may appear semi-transparent in the same scene as a White avatar who will appear more opaque. We present an exploratory user study ( N=160) investigating whether differing opacity levels result in dehumanizing avatar and human faces. Results support that dehumanization occurs as opacity decreases. This suggests that in similar lighting, low lightness skin tones (e.g., Black faces) will be viewed as less human than high lightness skin tones (e.g., White faces). Additionally, the perceived emotionality of virtual human faces also predicts perceived humanness. Angry faces were seen overall as less human, and at lower opacity levels happy faces were seen as more human. Our results suggest that additional research is needed to understand the effects and interactions of emotionality and opacity on dehumanization. Further, we provide evidence that unintentional racial bias may be added when developing for optical see-through devices using virtual humans. We highlight the potential bias and discuss implications and directions for future research.

Evidence of Racial Bias Using Immersive Virtual Reality: Analysis of Head and Hand Motions During Shooting Decisions.

Shooter bias is the tendency to more quickly shoot at unarmed Black suspects compared to unarmed White suspects. The primary goal of this research was to investigate the efficacy of shooter bias simulation studies in a more realistic immersive virtual scenario instead of the traditional methodologies using desktop computers. In this paper we present results from a user study (N=99) investigating shooter and racial bias in an immersive virtual environment. Our results highlight how racial bias was observed differently in an immersive virtual environment compared to previous desktop-based simulation studies. Latency to shoot, the standard shooter bias measure, was not found to be significantly different between race or socioeconomic status in our more realistic scenarios where participants chose to raise a weapon and pull a trigger. However, more nuanced head and hand motion analysis was able to predict participants' racial shooting accuracy and implicit racism scores. Discussion of how these nuanced measures can be used for detecting behavior changes for body-swap illusions, and implications of this work related to racial justice and police brutality are discussed.

The Impact of a Self-Avatar, Hand Collocation, and Hand Proximity on Embodiment and Stroop Interference.

Understanding the effects of hand proximity to objects and tasks is critical for hand-held and near-hand objects. Even though self-avatars have been shown to be beneficial for various tasks in virtual environments, little research has investigated the effect of avatar hand proximity on working memory. This paper presents a between-participants user study investigating the effects of self-avatars and physical hand proximity on a common working memory task, the Stroop interference task. Results show that participants felt embodied when a self-avatar was in the scene, and that the subjective level of embodiment decreased when a participant's hands were not collocated with the avatar's hands. Furthermore, a participant's physical hand placement was significantly related to Stroop interference: proximal hands produced a significant increase in accuracy compared to non-proximal hands. Surprisingly, Stroop interference was not mediated by the existence of a self-avatar or level of embodiment.

Mind the Gap: The Underrepresentation of Female Participants and Authors in Virtual Reality Research.

A common goal of human-subject experiments in virtual reality (VR) research is evaluating VR hardware and software for use by the general public. A core principle of human-subject research is that the sample included in a given study should be representative of the target population; otherwise, the conclusions drawn from the findings may be biased and may not generalize to the population of interest. In order to assess whether characteristics of participants in VR research are representative of the general public, we investigated participant demographic characteristics from human-subject experiments in the Proceedings of the IEEE Virtual Reality Conferences from 2015-2019. We also assessed the representation of female authors. In the 325 eligible manuscripts, which presented results from 365 human-subject experiments, we found evidence of significant underrepresentation of women as both participants and authors. To investigate whether this underrepresentation may bias researchers' findings, we then conducted a meta-analysis and meta-regression to assess whether demographic characteristics of study participants were associated with a common outcome evaluated in VR research: the change in simulator sickness following head-mounted display VR exposure. As expected, participants in VR studies using HMDs experienced small but significant increases in simulator sickness. However, across the included studies, the change in simulator sickness was systematically associated with the proportion of female participants. We discuss the negative implications of conducting experiments on non-representative samples and provide methodological recommendations for mitigating bias in future VR research.

A Steering Algorithm for Redirected Walking Using Reinforcement Learning.

Redirected Walking (RDW) steering algorithms have traditionally relied on human-engineered logic. However, recent advances in reinforcement learning (RL) have produced systems that surpass human performance on a variety of control tasks. This paper investigates the potential of using RL to develop a novel reactive steering algorithm for RDW. Our approach uses RL to train a deep neural network that directly prescribes the rotation, translation, and curvature gains to transform a virtual environment given a user's position and orientation in the tracked space. We compare our learned algorithm to steer-to-center using simulated and real paths. We found that our algorithm outperforms steer-to-center on simulated paths, and found no significant difference on distance traveled on real paths. We demonstrate that when modeled as a continuous control problem, RDW is a suitable domain for RL, and moving forward, our general framework provides a promising path towards an optimal RDW steering algorithm.

Evaluation of reorientation techniques and distractors for walking in large virtual environments.

Virtual Environments (VEs) that use a real-walking locomotion interface have typically been restricted in size to the area of the tracked lab space. Techniques proposed to lift this size constraint, enabling real walking in VEs that are larger than the tracked lab space, all require reorientation techniques (ROTs) in the worst-case situation-when a user is close to walking out of the tracked space. We propose a new ROT using visual and audial distractors-objects in the VE that the user focuses on while the VE rotates-and compare our method to current ROTs through three user studies. ROTs using distractors were preferred and ranked more natural by users. Our findings also suggest that improving visual realism and adding sound increased a user's feeling of presence. Users were also less aware of the rotating VE when ROTs with distractors were used. Our findings also suggest that improving visual realism and adding sound increased a user's feeling of presence.

Estimation of Rotation Gain Thresholds Considering FOV, Gender, and Distractors.

Redirected walking techniques enable users to naturally locomote in virtual environments (VEs) that are larger than the tracked space. Redirected walking imperceptibly transforms the VE around the user with predefined estimated threshold gains. Previously estimated gains were evaluated with a 40° field of view (FOV), and have not been evaluated in the presence of a distractor-a moving object in the VE that may capture the user's attention. We conducted a 2 (FOV: 40°, 110°) × 2 (Gender: female, male) × 2 (Distractor: without, with) user study to estimate and compare thresholds for rotation gains. Significant differences in detection thresholds were found between FOVs, and significant differences were found between female and male gains with a 110° FOV. Males had significantly wider gains using a 110° FOV compared to a 40° FOV, and distractors affected females differently than males. Finally, strong correlations were found between simulator sickness scores and threshold gains.

Avatar Embodiment. Towards a Standardized Questionnaire.

Inside virtual reality, users can embody avatars that are collocated from a first-person perspective. When doing so, participants have the feeling that the own body has been substituted by the self-avatar, and that the new body is the source of the sensations. Embodiment is complex as it includes not only body ownership over the avatar, but also agency, co-location, and external appearance. Despite the multiple variables that influence it, the illusion is quite robust, and it can be produced even if the self-avatar is of a different age, size, gender, or race from the participant's own body. Embodiment illusions are therefore the basis for many social VR experiences and a current active research area among the community. Researchers are interested both in the body manipulations that can be accepted, as well as studying how different self-avatars produce different attitudinal, social, perceptual, and behavioral effects. However, findings suggest that despite embodiment being strongly associated with the performance and reactions inside virtual reality, the extent to which the illusion is experienced varies between participants. In this paper, we review the questionnaires used in past experiments and propose a standardized embodiment questionnaire based on 25 questions that are prevalent in the literature. We encourage future virtual reality experiments that include first-person virtual avatars to administer this questionnaire in order to evaluate the degree of embodiment.

The Effect of Gender Body-Swap Illusions on Working Memory and Stereotype Threat.

The underrepresentation of women in technical and STEM fields is a well-known problem, and stereotype threatening situations have been linked to the inability to recruit and retain women into these fields. Virtual reality enables the unique ability to perform body-swap illusions, and research has shown that these illusions can change participant behavior. Characteristically people take on the traits of the avatar they are embodying. We hypothesized that female participants embodying male avatars when a stereotype threat was made salient would demonstrate stereotype lift. We tested our hypothesis through a between-participants user study in an immersive virtual environment by measuring working memory. Our results support that stereotype threat can be induced in an immersive virtual environment, and that stereotype lift is possible with fully-immersive body-swap illusions. Additionally, our results suggest that participants in a gender-swapped avatar without an induced stereotype threat have significantly impaired working memory; however, this impairment is lifted when a threat is made salient. We discuss possible theories as to why a body-swap illusion from a female participant into a male avatar would only increase working memory impairment when not under threat, as well as applications and future research directions. Our results offer additional insight into understanding the cognitive effects of body-swap illusions, and provide evidence that virtual reality may be an applicable tool for decreasing the gender gap in technology.

The design and evaluation of a large-scale real-walking locomotion interface.

Redirected Free Exploration with Distractors (RFEDs) is a large-scale real-walking locomotion interface developed to enable people to walk freely in Virtual Environments (VEs) that are larger than the tracked space in their facility. This paper describes the RFED system in detail and reports on a user study that evaluated RFED by comparing it to Walking-in-Place (WIP) and Joystick (JS) interfaces. The RFED system is composed of two major components, redirection and distractors. This paper discusses design challenges, implementation details, and lessons learned during the development of two working RFED systems. The evaluation study examined the effect of the locomotion interface on users' cognitive performance on navigation and wayfinding measures. The results suggest that participants using RFED were significantly better at navigating and wayfinding through virtual mazes than participants using walking-in-place and joystick interfaces. Participants traveled shorter distances, made fewer wrong turns, pointed to hidden targets more accurately and more quickly, and were able to place and label targets on maps more accurately, and more accurately estimate the virtual environment size.

An Evaluation of Navigational Ability Comparing Redirected Free Exploration with Distractors to Walking-in-Place and Joystick Locomotion Interfaces.

We report on a user study evaluating Redirected Free Exploration with Distractors (RFED), a large-scale, real-walking, locomotion interface, by comparing it to Walking-in-Place (WIP) and Joystick (JS), two common locomotion interfaces. The between-subjects study compared navigation ability in RFED, WIP, and JS interfaces in VEs that are more than two times the dimensions of the tracked space. The interfaces were evaluated based on navigation and wayfinding metrics and results suggest that participants using RFED were significantly better at navigating and wayfinding through virtual mazes than participants using walking-in-place and joystick interfaces. Participants traveled shorter distances, made fewer wrong turns, pointed to hidden targets more accurately and more quickly, and were able to place and label targets on maps more accurately. Moreover, RFED participants were able to more accurately estimate VE size.

Improved Redirection with Distractors: A Large-Scale-Real-Walking Locomotion Interface and its Effect on Navigation in Virtual Environments.

Users in virtual environments often find navigation more difficult than in the real world. Our new locomotion interface, Improved Redirection with Distractors (IRD), enables users to walk in larger-than-tracked space VEs without predefined waypoints. We compared IRD to the current best interface, really walking, by conducting a user study measuring navigational ability. Our results show that IRD users can really walk through VEs that are larger than the tracked space and can point to targets and complete maps of VEs no worse than when really walking.