Modeling Locomotion with Body Angular Movements in Virtual RealityThis study proposes a time prediction model for locomotion along a polyline path with body angular movements in Virtual Reality (VR). We divide such locomotion into two components: navigating in multiple line-segment paths and turning at line-segment intersections. In the first component, locomotion in each line-segment path consists of acceleration, maximum velocity, and deceleration phases. We formulated equations to estimate the locomotion time for each phase and then accumulated them to model the total time. In the second component, a linear relationship was revealed between task time and turning angles. We established an integrated model based on the equations of the two components and verified the effectiveness of the model with three experiments. The results indicate that our model outperformed two baseline models with a greater R^2 and a smaller gap between the predicted and actual time. Our study benefits VR locomotion design with body angular movements.2025ZMZijun Mai et al.Jinan University, College of Information Science and Technology/Cyber SecurityFull-Body Interaction & Embodied InputImmersion & Presence ResearchCHI
The Fidelity-based Presence Scale (FPS): Modeling the Effects of Fidelity on Sense of PresenceWithin the virtual reality (VR) research community, there have been several efforts to develop questionnaires with the aim of better understanding the sense of presence. Despite having numerous surveys, the community does not have a questionnaire that informs which components of a VR application contributed to the sense of presence. Furthermore, previous literature notes the absence of consensus on which questionnaire or questions should be used. Therefore, we conducted a Delphi study, engaging presence experts to establish a consensus on the most important presence questions and their respective verbiage. We then conducted a validation study with an exploratory factor analysis (EFA). The efforts between our two studies led to the creation of the Fidelity-based Presence Scale (FPS). With our consensus-driven approach and fidelity-based factoring, we hope the FPS will enable better communication within the research community and yield important future results regarding the relationship between VR system fidelity and presence.2025JBJacob Belga et al.University of Central FloridaImmersion & Presence ResearchVisualization Perception & CognitionPrototyping & User TestingCHI
Better, Funner, Stronger: A Gameful Approach to Nudge People into Making Less Predictable Graphical Password ChoicesGraphical user authentication (GUA) is a common alternative to text-based user authentication, where people are required to draw graphical passwords on background images. Such schemes are theoretically considered remarkably secure because they offer a large password space. However, people tend to create their passwords on salient image areas introducing high password predictability. Aiming to help people use the password space more effectively, we propose a gameful password creation process. In this paper, we present GamePass, a gamified mechanism that integrates the GUA password creation process. We provide the first evidence that it is possible to nudge people towards better password choices by gamifying the process. GamePass randomly guides participants' attention to areas other than the salient areas of authentication images, makes the password creation process more fun, and people are more engaged. Gamifying the password creation process enables users to interact better and make less predictable graphical password choices instead of being forced to use a strict password policy.2021GRGeorge E. Raptis et al.Human OpsisGamification DesignPasswords & AuthenticationDark Patterns RecognitionCHI
Distractor Effects on Crossing-Based InteractionTask-irrelevant distractors affect visuo-motor control for target acquisition and studying such effects has already received much attention in human-computer interaction. However, there has been little research into distractor effects on crossing-based interaction. We thus conducted an empirical study on pen-based interfaces to investigate six crossing tasks with distractor interference in comparison to two tasks without it. The six distractor-related tasks differed in movement precision constraint (directional/amplitude), target size, target distance, distractor location and target-distractor spacing. We also developed and experimentally validated six quantitative models for the six tasks. Our results show that crossing targets with distractors had longer average times and similar accuracy than that without distractors. The effects of distractors varied depending on distractor location, target-distractor spacing and movement precision constraint. When spacing is smaller than 11.27 mm, crossing tasks with distractor interference can be regarded as pointing tasks or a combination of pointing and crossing tasks, which could be better fitted with our proposed models than Fitts' law. According to these results, we provide practical implications to crossing-based user interface design.2021HTHuawei Tu et al.La Trobe UniversityUser Research Methods (Interviews, Surveys, Observation)Prototyping & User TestingCHI
Modeling the Endpoint Uncertainty in Crossing-based Moving Target SelectionModeling the endpoint uncertainty of moving target selection with crossing is essential to understand factors such as speed-accuracy trade-off and interaction efficiency in crossing-based user interfaces with dynamic contents. However, there have been few studies looking into this research topic in the HCI field. This paper presents a Quaternary-Gaussian model to quantitatively measure the endpoint uncertainty in crossing-based moving target selection. To validate this model, we conducted an experiment with discrete crossing tasks on five factors, i.e., initial distance, size, speed, orientation, and moving direction. Results showed that our model fit the data of ? and ? accurately with adjusted R2 of 0.883 and 0.920. We also demonstrated the validity of our model in predicting error rates in crossing-based moving target selection. We concluded with a set of implications for future designs.2020JHJin Huang et al.Institute of Software, Chinese Academy of Sciences & University of Chinese Academy of SciencesEye Tracking & Gaze InteractionContext-Aware ComputingCHI
Interrogating Social Virtual Reality as a Communication Medium for Older AdultsA growing body of research is examining the way that virtual reality (VR) technology might enrich the lives of older adults. However, no studies have yet examined how this technology–combining head mounted displays, motion tracking, avatars, and virtual environments–might contribute to older adult wellbeing by facilitating greater social participation (social VR). To address this gap, we conducted three workshops in which 25 older adults aged 70 to 81 explored the utility of social VR as a medium for communicating with other older adults. Participants first created embodied avatars that were controlled through natural gestures, and subsequently used these avatars in two high-fidelity social VR prototypes. Findings from the workshops provide insight into older adults' design motivations when creating embodied avatars for social VR; their acceptance of social VR as a communication tool; and their views on how social VR might play a beneficial role in their lives. Outcomes from the workshops also illustrate the critical importance our participants placed on behavioural anthropomorphism–the embodied avatars' ability to speak, move, and act in a human-like manner–alongside translational factors, which encapsulate issues relating to the way physical movements are mapped to the embodied avatar and the way in which errors in these mappings may invoke ageing stereotypes. Findings demonstrate the critical role that these characteristics might play in the success of future social VR applications targeting older users. We translate our findings into a set of design considerations for developing social VR systems for older adults, and we reflect on how our participants' experiences can inform future research on social virtual reality.2019SBSteven Baker et al.VR and immersive interfacesCSCW