In multilingual conferences, translation support should not compromise non‑verbal cues or social interaction. Prior work on eXtended Reality (XR) subtitles aids comprehension but rarely examines translation latency. We conducted a VR-simulated conference, testing latencies of 0, 1.5, 3, 4.5, and 6 seconds to measure overall comprehension and attribution of verbal and non‑verbal information. Results showed that latencies beyond 3 seconds significantly increased subjective difficulty and affected accuracy, while shorter latencies showed no significant effects. Furthermore, participants noted that very low delay drew attention to subtitles, reducing opportunities to observe the speaker. Guided by these insights, we designed and evaluated four VR subtitle interfaces, including one traditional and three novel designs. Across delay conditions, Merged Subtitles improved opportunities to observe the speaker and resulted in better emotion attribution and user experience than other designs. We also proposed design guidelines for XR subtitle interfaces based on different levels of translation latency.

Virtual Reality (VR) co-manipulation enables multiple users to collaboratively interact with shared virtual objects. However, existing research treats objects as monolithic entities, overlooking scenarios where users need to manipulate different sub-components simultaneously. This work addresses conflict resolution when users select overlapping vertices (non-disjoint sets) during co-manipulation. We present a comprehensive framework comprising preventive strategies (Object-level and Action-level Restrictions) and reactive strategies (computational conflict resolution). Through two user studies with 76 participants (38 pairs), we evaluated these approaches in collaborative wireframe editing tasks. Study 1 identified Averaging as the optimal computational method, balancing task efficiency with user experience. Study 2 highlighted that Action-level Restriction, which permits overlapping selections but restricts concurrent identical operations, achieved better performance compared to exclusive object locking. Reactive strategies using averaging provided smooth collaboration for experienced users, while second-user priority enabled quick corrections. Our findings indicate that optimal strategy selection depends on task requirements, user expertise, and collaboration patterns. Based on the findings, we provide design implications for developing VR collaboration systems that support flexible sub-components manipulation while maintaining collaborative awareness and minimizing conflicts.

Teleportation is a widely adopted locomotion technique in virtual reality (VR), with reorientation commonly integrated into commercial systems to reduce physical turning and improve navigational control. However, research on reorientation-enabled teleportation has received limited attention and still lacks clear design guidance, resulting in longer interaction times, greater complexity, and higher mental workload. To bridge this gap, we revisit reorientation-enabled teleportation through bare-hand interaction, a natural and device-free modality that is now increasingly supported and widely adopted in mainstream VR systems. Accordingly, four gesture-based techniques, Concurrent Wrist Rotation (C-WR), Decoupled Wrist Rotation (D-WR), Joystick Wrist Rotation (J-WR), and Direction Drawing (DD), were introduced and evaluated in a controlled user study with 24 participants. Results show that C-WR was fastest but error-prone, D-WR improved accuracy at the cost of time, J-WR supported precise orientation but was demanding and slow, while DD offered balanced performance and was most preferred overall. From these findings, four design implications were distilled, emphasizing efficiency, intuitive mappings, and support for diverse user preferences. Finally, two example extensions illustrate how these techniques may extend to broader VR applications.

High latency is often introduced due to limited computational capabilities and high hardware demands. It has proven to significantly impair user performance in target selection, a fundamental interaction task. Existing research has established that latency negatively impacts selection times and success rates in 2D interactive systems; however, the underlying behavioral mechanisms remain unclear. This article investigates the effects of latency on selection times, success rates, and endpoint distributions in Virtual Reality (VR) with controller-based raycasting and bare-hand direct touch-the two most common selection methods. Our results from a user study (N = 31) revealed distinct patterns between the two methods, leading to two novel mathematical models that account for latency, target width, and movement amplitude. These two models were validated via a new dataset collected from a second user study (N = 16) and were demonstrated to outperform the existing models. Our findings provide actionable recommendations to mitigate the negative impacts of latency and improve user experience in VR interface design.

Cursors and how they are presented significantly influence user experience in both VR and non-VR environments by shaping how users interact with and perceive interfaces. In traditional interfaces, cursors serve as a fundamental component for translating human movement into digital interactions, enhancing interaction accuracy, efficiency, and experience. The design and visibility of cursors can affect users' ability to locate interactive elements and understand system feedback. In VR, cursor manipulation is more complex than in non-VR environments, as it can be controlled through hand, head, and gaze movements. With the arrival of the Apple Vision Pro, the use of gaze-controlled non-visible cursors has gained some prominence. However, there has been limited exploration of the effect of this type of cursor. This work presents a comprehensive study of the effects of cursor visibility (visible versus invisible) in gaze-based interactions within VR environments. Through two user studies, we investigate how cursor visibility impacts user performance and experience across different confirmation mechanisms and tasks. The first study focuses on selection tasks, examining the influence of target width, movement amplitude, and three common confirmation methods (air tap, blinking, and dwell). The second study explores pursuit tasks, analyzing cursor effects under varying movement speeds. Our findings reveal that cursor visibility significantly affects both objective performance metrics and subjective user preferences, but these effects vary depending on the confirmation mechanism used and task type. We propose eight design implications based on our empirical results to guide the future development of gaze-based interfaces in VR. These insights highlight the importance of tailoring cursor metaphors to specific interaction tasks and provide practical guidance for researchers and developers in optimizing VR user interfaces.

Weight perception is essential for delivering compelling and realistic object interaction in VR systems. While existing pseudo-haptic techniques have enabled users to perceive virtual object weight without physical actuation, their application has primarily been limited to near-field, direct hand interaction. As VR systems continue to advance in fidelity and versatility, interactions with objects beyond arm's reach are becoming increasingly common. However, how weight perception can be introduced into such remote interactions, and whether it can enhance user immersion and experience, remains underexplored. To bridge this gap, we present RayFlex, a pseudo-haptic technique that conveys object weight in raycasting-based interaction through visual displacement and dynamic ray deformation. The technique was evaluated in two user studies, which examined its effectiveness in supporting weight discrimination and its impact on user experience across different interaction contexts. Results indicate that RayFlex leads to significant improvements in perceived realism, presence, and satisfaction, while maintaining usability. From the results, we derived two implications and an application guideline that can help design future VR systems.

Target selection is a fundamental interaction task in virtual reality (VR) systems, particularly for older adults who face unique challenges due to age-related declines in motor and cognitive abilities. While controller-based raycasting is widely used for its accuracy and efficiency, the design of selection feedback remains an open question, particularly in enhancing usability and accessibility for aging populations. In this study, we propose seven feedback techniques, including three uni-modal (visual, audio, haptic) and four multimodal (visual-audio, visual-haptic, audio-haptic, visual-audio-haptic) approaches. To evaluate these techniques, we conducted two user studies focusing on selection tasks in controlled and realistic scenarios. Our results indicate that visual-based feedback, particularly expansion techniques, significantly improves selection accuracy and user experience. Moreover, multimodal feedback does not always yield better performance; rather, a combination of visual and haptic feedback provides the most effective balance between usability and cognitive load. Based on our findings, we derive six design implications to guide the development of VR selection feedback tailored to older adults. This work contributes to the understanding of optimal selection feedback mechanisms, promoting more inclusive and accessible VR interactions for aging users.

Prior work has shown that frame rate significantly influences user behavior in fast-response tasks in 2D and 3D contexts. However, its impact on a steering task, which involves navigating an object along a path from the start to the end, remains relatively unexplored, especially in the context of virtual reality (VR). This task is considered a typical non-fast-response activity, as it does not demand rapid reactions within a limited time frame. Our work aims to understand and model users' steering behavior and predict movement time with different task complexities and frame rates in VR environments. We first conducted a user study to collect user behavior in a steering task with four factors: frame rate, path length, width, and radius of curvature. Based on the results, we then quantified the effects of frame rate and built two predictive models. Our models exhibited the best fit ($r^{2}> 0.957$r2>0.957) and over 17% improvement in prediction accuracy for movement time compared to existing models. Our models' robustness was further validated by applying them to predict steering performance with different VR tasks and frame rates. The two models keep the best predictability for both movement time and speed.

This work explores the design of stick-shaped Tangible User Interfaces (TUI) for Extended Reality (XR). While sticks are widely used in everyday objects, their applications as a TUI in XR have not been systematically studied. We conducted a participatory design session with twelve experts in XR and human-computer interaction to investigate the affordances of stick-based objects and how to utilize them in XR. The results led us to develop a taxonomy of stick-based objects’ affordances in terms of their functions and holding gestures. Following that, we proposed four types of stick-based XR controller forms and discussed their advantages and limitations. In the end, we juxtaposed twenty-six existing XR controllers against our proposed forms and identified Landed (Cane) Stick, Thin Stick’s flexible usages, and Modular Design as the major opportunities that remain unexamined yet for stick-based XR TUI design.

Text selection is a common task in interactive systems. Often, it can be difficult because the letters and words are too small and clustered together to allow precise selection. Compared to traditional 2D interfaces, text selection is more challenging in virtual reality (VR) head-mounted displays (HMDs) because users interact with the immersive 3D space via mid-air interaction, which has higher degrees of freedom but becomes more imprecise and involves a higher workload due to the lack of support from a fixed structure like a desk. There has been limited exploration of techniques that support precise and rapid text selection at the character, word, sentence, or paragraph levels in VR HMDs. To fill this gap, we propose three controller-based text selection methods: Joystick Movement, Depth Movement, and Wrist Orientation. They are evaluated against a baseline selection method via a user study with 24 participants. Results show that the three proposed techniques significantly improved the performance and user experience over the baseline, especially for the selection beyond the character level.

Object selection is essential in virtual reality (VR) head-mounted displays (HMDs). Prior work mainly focuses on enhancing and evaluating techniques for selecting a single object in VR, leaving a gap in the techniques for multi-object selection, a more complex but common selection scenario. To enable multi-object selection, the interaction technique should support group selection in addition to the default pointing selection mode for acquiring a single target. This composite interaction could be particularly challenging when using freehand gestural input. In this work, we present an empirical comparison of six freehand techniques, which are comprised of three mode-switching gestures (Finger Segment, Multi-Finger, and Wrist Orientation) and two group selection techniques (Cone-casting Selection and Crossing Selection) derived from prior work. Our results demonstrate the performance, user experience, and preference of each technique. The findings derive three design implications that can guide the design of freehand techniques for multi-object selection in VR HMDs.

Alphanumeric and special characters are essential during text entry. Text entry in virtual reality (VR) is usually performed on a virtual Qwerty keyboard to minimize the need to learn new layouts. As such, entering capitals, symbols, and numbers in VR is often a direct migration from a physical/touchscreen Qwerty keyboard-that is, using the mode-switching keys to switch between different types of characters and symbols. However, there are inherent differences between a keyboard in VR and a physical/touchscreen keyboard, and as such, a direct adaptation of mode-switching via switch keys may not be suitable for VR. The high flexibility afforded by VR opens up more possibilities for entering alphanumeric and special characters using the Qwerty layout. In this work, we designed two controller-based raycasting text entry methods for alphanumeric and special characters input (Layer-ButtonSwitch and Key-ButtonSwitch) and compared them with two other methods (Standard Qwerty Keyboard and Layer-PointSwitch) that were derived from physical and soft Qwerty keyboards. We explored the performance and user preference of these four methods via two user studies (one short-term and one prolonged use), where participants were instructed to input text containing alphanumeric and special characters. Our results show that Layer-ButtonSwitch led to the highest statistically significant performance, followed by Key-ButtonSwitch and Standard Qwerty Keyboard, while Layer-PointSwitch had the slowest speed. With continuous practice, participants' performance using Key-ButtonSwitch reached that of Layer-ButtonSwitch. Further, the results show that the key-level layout used in Key-ButtonSwitch led users to parallel mode switching and character input operations because this layout showed all characters on one layer. We distill three recommendations from the results that can help guide the design of text entry techniques for alphanumeric and special characters in VR.

Users' perceived image quality of virtual reality head-mounted displays (VR HMDs) is determined by multiple factors, including the HMD's structure, optical system, display and render resolution, and users' visual acuity (VA). Existing metrics such as pixels per degree (PPD) have limitations that prevent accurate comparison of different VR HMDs. One of the main limitations is that not all VR HMD manufacturers released the official PPD or details of their HMDs' optical systems. Without these details, developers and users cannot know the precise PPD or calculate it for a given HMD. The other issue is that the visual clarity varies with the VR environment. Our work has identified a gap in having a feasible metric that can measure the visual clarity of VR HMDs. To address this gap, we present an end-to-end and user-centric visual clarity metric, omnidirectional virtual visual acuity (OVVA), for VR HMDs. OVVA extends the physical visual acuity chart into a virtual format to measure the virtual visual acuity of an HMD's central focal area and its degradation in its noncentral area. OVVA provides a new perspective to measure visual clarity and can serve as an intuitive and accurate reference for VR applications sensitive to visual accuracy. Our results show that OVVA is a simple yet effective metric for comparing VR HMDs and environments.

Target selection is a fundamental task in interactive Augmented Reality (AR) systems. Predicting the intended target of selection in such systems can provide users with a smooth, low-friction interaction experience. Our work aims to predict gaze-based target selection in AR headsets with eye and head endpoint distributions, which describe the probability distribution of eye and head 3D orientation when a user triggers a selection input. We first conducted a user study to collect users’ eye and head behavior in a gaze-based pointing selection task with two confirmation mechanisms (air tap and blinking). Based on the study results, we then built two models: a unimodal model using only eye endpoints and a multimodal model using both eye and head endpoints. Results from a second user study showed that the pointing accuracy is improved by approximately 32% after integrating our models into gaze-based selection techniques.

Region selection is a fundamental task in interactive systems. In 2D user interfaces, users typically use a rectangle selection tool to formulate a region using a mouse or touchpad. Region selection in 3D spaces, especially in Augmented Reality (AR) Head-Mounted Displays (HMDs) is different and challenging because users need to select an intended region via freehand mid-air gestures or eye-based actions that are touchless interactions. In this work, we aim to fill in the gap in the design of region selection techniques in AR HMDs. We first analyzed and discretized the interaction procedure of region selection and explored design possibilities for each step. We then developed four techniques for region selection in AR HMDs, which leveraged users' hand and gaze for unimodal or multimodal interaction. The techniques were evaluated via a user study with a controlled region selection task. The findings led to three design recommendations and two proof-of-concept application examples.

The refresh rate of virtual reality (VR) head-mounted displays (HMDs) has been growing rapidly in recent years because of the demand to provide higher frame rate content as it is often linked with a better experience. Today's HMDs come with different refresh rates ranging from 20Hz to 180Hz, which determines the actual maximum frame rate perceived by users' naked eyes. VR users and content developers often face a choice because having high frame rate content and the hardware that supports it comes with higher costs and other trade-offs (such as heavier and bulkier HMDs). Both VR users and developers can choose a suitable frame rate if they are aware of the benefits of different frame rates in user experience, performance, and simulator sickness (SS). To our knowledge, limited research on frame rate in VR HMDs is available. In this paper, we aim to fill this gap and report a study with two VR application scenarios that compared four of the most common and highest frame rates currently available (60, 90, 120, and 180 frames per second (fps)) to explore their effect on users' experience, performance, and SS symptoms. Our results show that 120fps is an important threshold for VR. After 120fps, users tend to feel lower SS symptoms without a significant negative effect on their experience. Higher frame rates (e.g., 120 and 180fps) can ensure better user performance than lower rates. Interestingly, we also found that at 60fps and when users are faced with fast-moving objects, they tend to adopt a strategy to compensate for the lack of visual details by predicting or filling the gaps to try to meet the performance needs. At higher fps, users do not need to follow this compensatory strategy to meet the fast response performance requirements.

Virtual reality head-mounted displays (VR HMDs) have become a popular platform for gaming. However, simulator sickness (SS) is still an impediment to VR’s wider adoption, particularly in gaming. It can induce strong discomfort and impair players’ immersion, performance, and enjoyment. Researchers have explored techniques to mitigate SS. While these techniques have been shown to help lessen SS, they may not be applicable to games because they cannot be easily integrated into various types of games without impacting gameplay, immersion, and performance. In this research, we introduce a new SS mitigation technique, VRCockpit. VRCockpit is a visual technique that surrounds the player with four 2D views, one for each cardinal direction, that show 2D copies of the areas of the 3D environment around the player. To study its effectiveness, we conducted two different experiments, one with a car racing game, followed by a first-person shooter game. Our results show that VRCockpit has the potential to mitigate SS and still allows players to have the same level of immersion and gameplay performance.

This paper investigates integration, coordination, and transition strategies of gaze and hand input for 3D object manipulation in VR. Specifically, this work aims to understand whether incorporating gaze input can benefit VR object manipulation tasks, and how it should be combined with hand input for improved usability and efficiency. We designed four gaze-supported techniques that leverage different combination strategies for object manipulation and evaluated them in two user studies. Overall, we show that gaze did not offer significant performance benefits for transforming objects in the primary working space, where all objects were located in front of the user and within the arm-reach distance, but can be useful for a larger environment with distant targets. We further offer insights regarding combination strategies of gaze and hand input, and derive implications that can help guide the design of future VR systems that incorporate gaze input for 3D object manipulation.

Mode-switching supports multilevel operations using a limited number of input methods. In Virtual Reality (VR) head-mounted displays (HMD), common approaches for mode-switching use buttons, controllers, and users’ hands. However, they are inefficient and challenging to do with tasks that require both hands (e.g., when users need to use two hands during drawing operations). Using head gestures for mode-switching can be an efficient and cost-effective way, allowing for a more continuous and smooth transition between modes. In this paper, we explore the use of head gestures for mode-switching especially in scenarios when both users’ hands are performing tasks. We present a first user study that evaluated eight head gestures that could be suitable for VR HMD with a dual-hand line-drawing task. Results show that move forward, move backward, roll left, and roll right led to better performance and are preferred by participants. A second study integrating these four gestures in Tilt Brush, an open-source painting VR application, is conducted to further explore the applicability of these gestures and derive insights. Results show that Tilt Brush with head gestures allowed users to change modes with ease and led to improved interaction and user experience. The paper ends with a discussion on some design recommendations for using head-based mode-switching in VR HMD.