We present Pluskin, a machine-embroidered plush skin that transforms the surface of a companion robot dog into a soft tactile sensing interface. Fabricated via digital loop-pile embroidery, Pluskin provides a scalable sensing solution that integrates the softness and familiarity of plush materials with textile-based sensing. We implemented a 4 × 3 sensing array on the dorsal surface of a Petoi Bittle robotic dog to validate the system. Using a Support Vector Machine (SVM) classifier on extracted spatiotemporal voltage features, the system identifies five natural touch gestures and maps them to corresponding embodied robot behaviors. By integrating plush materiality, tactile sensing, and embodied robot feedback, this work demonstrates a feasible approach toward a more natural and affective human-robot interaction interface.

Throughput is a widely used performance metric, combining speed and accuracy into a single measure, while reducing the effect of subjective speed–accuracy trade-offs. Despite its wide application in 2D steering tasks, its direct extension to 3D presents unique challenges since 3D trajectories exhibit higher variability, and perceptual–motor factors undermine existing formulations. Consequently, throughput has not been systematically adopted for evaluating steering in 3D virtual environments. In this paper, using a controlled virtual reality user study with a ring-and-wire task, we introduce and validate a novel throughput formulation for 3D steering based on the bivariate standard deviation of the trajectory for the effective width calculation. Our results show that this formulation provides smoother throughput values across subjective speed–accuracy differences and improves model fit compared to traditional approaches. This work advances our theoretical understanding of the Steering law in 3D contexts, provides researchers and practitioners with a robust evaluation method, and establishes a foundation for future studies of complex 3D trajectory interactions.

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.

Perceptual grouping enables people to organize elements into units according to intrinsic (e.g., proximity) and extrinsic (e.g., common region) principles. However, the role of physical surfaces as extrinsic grouping cues for virtual elements in Augmented Reality (AR) remains unclear. To provide a deeper understanding, we conducted two within-subject studies. The first study (N = 24) using repetition discrimination tasks revealed that surfaces can be common-region cues in 3D, with their influence depending on their distance to target objects along the viewing direction. Building on these findings, the second study (N = 24) employed both objective and subjective measures to capture the interaction between proximity and common-region cues in AR. Results indicate that competing cues reduce group clarity. They also enable us to distill people’s strategies for improving the clarity by leveraging their physical and virtual environments. Finally, we propose design recommendations for future AR systems in assisted grouping tasks.

The recent emergence and popularity of consumer-grade augmented reality (AR) glasses from major technology companies highlight their potential to become the next daily computing platform. A dominant design trend in this context is the integration of a front-facing camera to deliver a first-person perspective. While this approach is intuitive, there is limited evidence that it is optimal (or sufficient) for supporting users in daily tasks. This paper explores a more effective camera interaction technique for AR glasses, which we term "FlexiCamAR". This novel method aims to enhance both efficiency and the range of applications for AR glasses by offering flexible and comfortable secondary camera viewpoints. To investigate the applicability and usability of this approach, we developed a ring camera prototype that can be attached to users’ fingers. We then conducted a user study with 12 participants, comparing FlexiCamAR against the baseline, a traditional front-facing AR camera setup, across two common tasks: taking photos and scanning QR codes. Our findings show that FlexiCamAR significantly reduces physical load. We also explore potential scenarios where the additional viewpoint afforded by FlexiCamAR proves valuable, such as capturing low-angle perspectives or navigating confined spaces. Participant feedback further suggests strong potential for additional applications, including selfie taking, video conferencing, and object scanning. Overall, FlexiCamAR presents a novel interaction approach that can serve as a powerful supplement or alternative to the first-person perspective, significantly improving the adaptability of AR glasses for everyday use.

We present ScaleFree, a GPU-accelerated adaptive Kernel Density Estimation (KDE) algorithm for scalable, interactive multiscale point cloud exploration. With this technique, we cater to the massive datasets and complex multiscale structures in advanced scientific computing, such as cosmological simulations with billions of particles. Effective exploration of such data requires a full 3D understanding of spatial structures, a capability for which immersive environments such as VR are particularly well suited. However, simultaneously supporting global multiscale context and fine-grained local detail remains a significant challenge. A key difficulty lies in dynamically generating continuous density fields from point clouds to facilitate the seamless scale transitions: while KDE is widely used, precomputed fields restrict the accuracy of interaction and omit fine-scale structures, while dynamic computation is often too costly for real-time VR interaction. We address this challenge by leveraging GPU acceleration with k-d-tree-based spatial queries and parallel reduction within a thread group for on-the-fly density estimation. With this approach, we can recalculate scalar fields dynamically as users shift their focus across scales. We demonstrate the benefits of adaptive density estimation through two data exploration tasks: adaptive selection and progressive navigation. Through performance experiments, we demonstrate that ScaleFree with GPU-parallel implementation achieves orders-of-magnitude speedups over sequential and multi-core CPU baselines. In a controlled experiment, we further confirm that our adaptive selection technique improves accuracy and efficiency in multiscale selection tasks.

The development of virtual reality (VR) technology has allowed virtual museums to enrich experiences of personal memories. In this work, we first conducted a survey study to understand the way people use to record, store, and share their digital memories. Informed by the results, we present MemoryVR, a personal virtual museum system designed to preserve and share digital memories. It allows individuals to organize and share their own memories in a virtual museum environment and to visit the memory spaces of others in an immersive way. We invited participants to experience MemoryVR and analyzed their behavior and expectations. The evaluation results showed that users perceived excellent pragmatic and hedonic qualities of MemoryVR. Participants found their experiences of memories in personal virtual museums to be fulfilling. Additionally, we gathered suggestions from participants about MemoryVR, providing design recommendations for customized personal virtual museums.

With the rapid advancement of AI systems, their abilities to store, retrieve, and utilize information over the long term - referred to as long-term memory - have become increasingly significant. These capabilities are crucial for enhancing the performance of AI systems across a wide range of tasks. However, there is currently no comprehensive survey that systematically investigates AI's long-term memory capabilities, formulates a theoretical framework, and inspires the development of next-generation AI long-term memory systems. This paper begins by introducing the mechanisms of human long-term memory, then explores AI long-term memory mechanisms, establishing a mapping between the two. Based on the mapping relationships identified, we extend the current cognitive architectures and propose the Cognitive Architecture of Self-Adaptive Long-term Memory (SALM). SALM provides a theoretical framework for the practice of AI long-term memory and holds potential for guiding the creation of next-generation long-term memory driven AI systems. Finally, we delve into the future directions and application prospects of AI long-term memory.

Cross Reality (CR) is a new emerging field based on the current developments in Mixed Reality hardware, especially supported by the broad market penetration of video-based see-through Head-Mounted Displays. It refers to applications that span across different stages (real, Augmented Reality, Augmented Virtuality, Virtual Reality) of the reality-virtuality continuum, where users are interconnected between different stages and/or are able to transition between these stages. This publication follows the concept of other grand challenges publications and reflects the discussion of various researchers invested in CR. After an initial discussion at the 1stJoint Workshop on Cross Reality at IEEE ISMAR 2023, six topic groups have been identified, leading to 22 challenges, which were discussed in groups over the period of multiple months. The discussion of these challenges should act as a road map for future research in the area of CR.

Augmented reality (AR) assembly guidance systems can help users quickly master the assembly process of unfamiliar objects. However, it is very difficult for practical use without a thorough understanding of users' intentions. Furthermore, existing approaches still struggle to handle complex hand-part interactions and nonlinear assembly steps, and achieving intuitive and real-time guidance remains challenging. To address these issues, we propose an intention-driven camera-projector AR assembly guidance system (IntentionAR) that integrates online user intention inference with a finite-state assembly machine. The intention module recognizes interaction actions and infers the target object, enabling feedback before assembly begins, while the finite state machine (FSM) manages step progression. Using a camera-projector device, the system highlights candidate parts and, based on inferred intention, flags correct/incorrect selections to provide real-time guidance. As the assembly progresses, the models used for spatial registration and visualization switch dynamically to accommodate the nonlinear workflow. Experiments and user studies show that the system delivers a more robust AR interaction experience and improves assembly efficiency. A free copy of this paper and all supplemental materials, as well as project assets and source code, will be available at the project website.

Intergenerational households often involve children and older adults sharing daily life. Yet, it remains challenging to find shared exercise activities due to the significant differences in motor ability, motivational preferences, and user experience needs. Existing exergames lower the entry barriers through body-based interaction, but screen-based setups restrict play to indoor environments. XR HMDs extend exergames into public contexts, yet the differential impact of VR and MR on intergenerational play remains underexplored. To address this gap, we developed an asymmetric-role XR exergame and conducted a $2\times 2$ within-subjects study with 20 intergenerational pairs (N=40) to explore the effect of Display Mode (VR vs MR) and Environmental Context (Private Space vs Public Space) on their user experience and collaborative performance. This work reveals clear age-related patterns: children exhibited greater engagement in immersive VR environments, whereas older adults preferred MR for improved safety and enhanced visibility of their intergenerational partners. Finally, we offer design guidelines for leveraging complementary strengths of XR display modes and environmental contexts to support inclusive and engaging intergenerational exergames.

Amid the global decline in news credibility, immersive journalism in virtual reality (VR) offers opportunities to enhance trust and engagement through presence and interactivity. As the communicators of news, virtual news anchors play a key role in shaping audience perceptions. However, the mechanisms through which virtual anchors in VR elicit audience trust remain underexplored. Guided by the Stimulus-Organism-Response framework, this study investigates how the visual style and voiceover of VR news avatars influence perceived realism, and how these perceptions subsequently shape trust and news credibility. In a $2 \times 2$ within-subjects experiment $(N = 24)$, participants viewed a virtual news anchor featuring either (1) a realistic or (2) a cartoon-like visual style, paired with either (1) an anthropomorphic or (2) a neutral voiceover. Results indicate that visual style exerted a dominant influence on perceived realism and trust in virtual anchors. By contrast, while voiceover type did not affect perceived realism, perceived voice realism significantly predicted trust, highlighting the nuanced role of vocal cues in VR news contexts. Notably, the interaction between visual and vocal realism failed to yield an additive effect on trust, and avatar trust did not significantly predict news credibility. Our findings shed further light on avatar trust in immersive news environments and provide design insights for the development of credible and trustworthy virtual anchors.

The Video See-Through (VST) technology in Extended Reality Head-Mounted Displays (XR HMDs) allows users to perceive the real-world environment while viewing seamlessly integrated virtual content in passthrough mode. This technology has demonstrated significant potential across domains such as industry, healthcare, and intelligent driving. However, the camera of current VST technologies often struggles with visual fidelity, especially in low-light environments. To address this challenge, we introduce NoctuaXR, a lightweight, low-cost, environment-aware enhancement that dynamically adjusts the pixel-level brightness and saturation of the VST view in real time based on ambient light conditions, significantly improving visual quality in low-light scenarios. In a 10 lx environment, which is a very dim level of light, our tests show that NoctuaXR improves the color accuracy of the Baseline by 68.59% and outperforms the current leading, professional XR HMD, the Varjo XR-4 Focal Edition, by 64.26%. Furthermore, a comprehensive evaluation, including a perceptual quality evaluation and a daily task performance evaluation, confirms NoctuaXR's effectiveness. Our method provides users with a significantly improved visual experience, elevating their task efficiency to a level comparable to the Varjo XR-4. We also present compelling real-world use cases-from in-flight entertainment to navigating a dark room without disturbing others-that highlight NoctuaXR's tangible value in making XR technology safer, more convenient, and truly practical for daily life.

Virtual reality (VR) allows users to observe and manipulate 3D geometry from multiple viewpoints. Most VR selection work, however, optimizes techniques for selecting entire objects. Selecting a single face on a polyhedron remains underexplored and is more challenging because the interaction must act on a local component while preserving the object's global structure. We introduce a design space tailored to this task with three dimensions: viewing strategy, disambiguation consistency, and interaction metaphor. Guided by this space, we design eight freehand techniques for polyhedral face selection. A within-subjects study with 16 participants evaluates these techniques across polyhedral complexity (two radii; face counts 4, 6, and 12). The results identify three complementary top techniques, reveal tradeoffs between viewing choices and geometric preservation, and yield concrete guidelines for matching techniques to target geometry and task demands. A follow-up study with complex, realistic models confirms the robustness and practical usability of the three techniques. Together, these contributions shift attention from whole object selection to precise component selection in VR and provide actionable methods for 3D modeling, assembly, and texturing.

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.

Teleportation is widely used in Virtual Reality (VR) applications, especially for enabling efficient navigation in large-scale virtual environments. Leveraging foot movements for teleportation frees the hands for parallel tasks and helps maintain spatial orientation, making it particularly suitable for seated and multitasking VR scenarios. This work explores feasible foot actions for teleportation in confined seating conditions, such as traveling on an airplane or train, where users' leg motion is feasible, but its range is constrained. Such scenarios are common but are underexplored. We propose seven metaphor-inspired teleportation techniques based on foot interactions and evaluate their effectiveness through a user study. The findings provide valuable insights for designing effective teleportation techniques in VR scenarios where users are seated in constrained spaces.

Virtual reality (VR) users often encounter interruptions, posing challenges to maintaining real-world awareness during immersive experiences. The Passthrough feature in VR headsets allows users to view their physical surroundings without removing the headset. However, when interruptions come from the rear, users need to turn their heads to see the real world, which can lead to negative experiences in VR. Study 1, conducted through semi-structured interviews involving 13 participants, found that users are less likely to use Passthrough for rear interruptions due to large head-turning movements, which cause inconvenience, increase the risk of motion sickness, and reduce the experience. Building on these findings, we introduced three Passthrough techniques in Study 2 for displaying the rear view in front of the user: Full Rear Passthrough + Pause (FRPP), Rear Passthrough Window (RPW), and Rear Passthrough AR (RPAR). Compared to the Baseline method that requires head-turning, all three systems reduced physical and temporal demands, alleviated disorientation caused by motion sickness, and provided a better user experience for managing rear interruptions. Among these, FRPP and RPAR were the most preferred. These findings provide valuable insights for future VR design, emphasizing the need for solutions that effectively manage rear interruptions while maintaining user comfort and experience.

Proximity-based feedback provides users with real-time guidance as they approach an interaction goal. This type of feedback is particularly useful for tasks that require guidance during the interaction process, such as selecting moving targets. This work explores proximity-based feedback types and modalities to improve the selection of moving targets in VR by leveraging three feedback types that combine visual, auditory, and haptic modalities. We evaluated the performance of these mechanisms through two user studies, analyzing both objective data (e.g., selection time, error rate) and subjective data (e.g., user experience, preferences) to explore the characteristics of feedback types across different modalities and to examine the roles of various modalities within multimodal combinations. Our findings suggest optimal selection mechanisms for developers and should be tailored to different goals: achieving user precision, enabling quick movement to a target, considering task duration, and enhancing entertainment value. We also discuss applications that correspond to these different perspectives.

Target selection is one of the most fundamental tasks in VR interaction systems. Prediction heuristics can provide users with a smoother interaction experience in this process. Our work aims to predict the ray landing pose for hand-based raycasting selection in Virtual Reality (VR) using a Long Short-Term Memory (LSTM)-based neural network with time-series data input of speed and distance over time from three different pose channels: hand, Head-Mounted Display (HMD), and eye. We first conducted a study to collect motion data from these three input channels and analyzed these movement behaviors. Additionally, we evaluated which combination of input modalities yields the optimal result. A second study validates raycasting across a continuous range of distances, angles, and target sizes. On average, our technique’s predictions were within 4.6° of the true landing Pose when 50% of the way through the movement. We compared our LSTM neural network model to a kinematic information model and further validated its generalizability in two ways: by training the model on one user’s data and testing on other users (cross-user) and by training on a group of users and testing on entirely new users (unseen users). Compared to the baseline and a previous kinematic method, our model increased prediction accuracy by a factor of 3.5 and 1.9, re spectively, when 40% of the way through the movement.

Steering involves continuous movement along constrained paths, well-studied in 2D. The extensions to 3D using the Ring-and-Wire and Ball-and-Tunnel tasks were often treated as interchangeable in previous work. In this paper, we directly compare these two tasks through a within-subjects user study (n = 18) with varying 3D path orientations. The results show that Ring-and-Wire significantly outperformed Ball-and-Tunnel, with 17.17% lower task time, 21.65% higher throughput, and 21.52% faster average speed. Participants also preferred Ring-and-Wire and reported lower workload. Visual ambiguity, especially near the tunnel’s rear surface, complicated spatial perception in the Ball-and-Tunnel task. We thus recommend that future studies choose 3D steering tasks carefully for experiments, as the two tasks are not interchangeable.

The advent of web-based interactive technologies has opened up new possibilities for virtual gatherings in 3D environments. Live-streaming, in particular, has gained increasing attention due to its effectiveness in engaging a large number of users in collective online activities. With an emphasis on audience participation, live-streaming shares common characteristics of the outlook of the metaverse and is driving new waves of interaction in virtual gatherings, such as engaging users through crowdsourcing control. However, this type of social interaction has not been examined in the Asian context, and it lacks systematic investigation of user experience with different crowdsourcing control methods. In this paper, we present a novel crowdsourcing control method based on DanMu, the subtitle system of Bilibili, one of the most successful and prevalent live-streaming platforms in Asia. We organized virtual gatherings by live-streaming a Minecraft virtual campus and examined the use of DanMu for crowdsourcing control. Our first study investigated the influence of three crowdsourcing control methods (First Come First Served, Vote, and Super Command) on collective navigation task efficiency and user experience. These influences were further discussed with user activeness and group sizes in a follow-up study. The results showed that Super Command, a representative mode on top of the democratic voting mechanism, offers better user experiences and social richness in large groups. Participants also rated its usability higher in small groups. Besides, virtual gathering in small groups allows greater pragmatic quality, usability, and a sense of agency than in large groups. Our work provides design guidelines for developers and HCI practitioners to develop crowdsourcing control methods and improve novel virtual gathering experiences in virtual worlds and the future metaverse.

Recent advances in eye-tracking technology have positioned gaze as an efficient and intuitive input method for Virtual Reality (VR), offering a natural and immersive user experience. As a result, gaze input is now leveraged for fundamental interaction tasks such as selection, manipulation, crossing, and steering. Although several studies have modeled user steering performance across various path characteristics and input methods, our understanding of gaze-based steering in VR remains limited. This gap persists because the unique qualities of eye movements-involving rapid, continuous motions-and the variability in eye-tracking make findings from other input modalities nontransferable to a gaze-based context, underscoring the need for a dedicated investigation into gaze-based steering behaviors and performance. To bridge this gap, we present two user studies to explore and model gaze-based steering. In the first one, user behavior data are collected across various path characteristics and eye-tracking conditions. Based on this data, we propose four refined models that extend the classic Steering Law to predict users' movement time in gaze-based steering tasks, explicitly incorporating the impact of tracking quality. The best-performing model achieves an adjusted R2 of 0.956, corresponding to a 16% improvement in movement time prediction. This model also yields a substantial reduction in AIC (from 1550 to 1132) and BIC (from 1555 to 1142), highlighting improved model quality and better balance between goodness of fit and model complexity. Finally, data from a second study with varied settings, such as a different eye-tracking sampling rate, illustrate the strong robustness and predictability of our models. Finally, we present scenarios and applications that demonstrate how our models can be used to design enhanced gaze-based interactions in VR systems.

The viewing experience of 3D artifacts in Virtual Reality (VR) museums is constrained and affected by various factors, such as pedestal height, viewing distance, and object scale. User experiences regarding these factors can vary subjectively, making it difficult to identify a universal optimal solution. In this paper, we collect empirical data on user-determined parameters for the optimal viewing experience in VR museums. By modeling users' viewing behaviors in VR museums, we derive predictive functions that configure the pedestal height, calculate the optimal viewing distance, and adjust the appropriate handheld scale for the optimal viewing experience. This led to our novel 3D responsive design, ResponsiveView. Similar to the responsive web design that automatically adjusts for different screen sizes, ResponsiveView automatically adjusts the parameters in the VR environment to facilitate users' viewing experience. The design has been validated with two popular inputs available in current commercial VR devices: controller-based interactions and hand tracking, demonstrating enhanced viewing experience in VR museums.

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.

Virtual co-embodiment in virtual reality (VR) allows two users to share an avatar, enabling skill transfer from teachers to learners and influencing their Sense of Ownership (SoO) and Sense of Agency (SoA). However, mismatches between actual movements and displayed actions in VR can impair user experience, posing challenges to learning effectiveness. Although previous studies have addressed the influence of virtual bodies' visual factors on SoO and SoA, the impact of co-embodied hands' appearances remains underexplored. We conducted two user studies to examine the effects of virtual self-hands' existence and their visual factors (transparency and congruency) on SoO, SoA, and social presence. Study One showed significant improvements in SoO and SoA with the existence of virtual self-hands. In Study Two, we kept the self-hands and further focused on hand transparency and congruency. We found that identical appearances between self-hands and co-embodied hands significantly enhanced SoO. These findings stressed the importance of visual factors for virtual hands, offering valuable insights for VR co-embodiment design.

We propose and study a novel cross-reality environment that seamlessly integrates a monoscopic 2D surface (an interactive screen with touch and pen input) with a stereoscopic 3D space (an augmented reality HMD) to jointly host spatial data visualizations. This innovative approach combines the best of two conventional methods of displaying and manipulating spatial 3D data, enabling users to fluidly explore diverse visual forms using tailored interaction techniques. Providing such effective 3D data exploration techniques is pivotal for conveying its intricate spatial structures-often at multiple spatial or semantic scales-across various application domains and requiring diverse visual representations for effective visualization. To understand user reactions to our new environment, we began with an elicitation user study, in which we captured their responses and interactions. We observed that users adapted their interaction approaches based on perceived visual representations, with natural transitions in spatial awareness and actions while navigating across the physical surface. Our findings then informed the development of a design space for spatial data exploration in cross-reality. We thus developed cross-reality environments tailored to three distinct domains: for 3D molecular structure data, for 3D point cloud data, and for 3D anatomical data. In particular, we designed interaction techniques that account for the inherent features of interactions in both spaces, facilitating various forms of interaction, including mid-air gestures, touch interactions, pen interactions, and combinations thereof, to enhance the users' sense of presence and engagement. We assessed the usability of our environment with biologists, focusing on its use for domain research. In addition, we evaluated our interaction transition designs with virtual and mixed-reality experts to gather further insights. As a result, we provide our design suggestions for the cross-reality environment, emphasizing the interaction with diverse visual representations and seamless interaction transitions between 2D and 3D spaces.

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.

Tangible interfaces in mixed reality (MR) environments allow for intuitive data interactions. Tangible cubes, with their rich interaction affordances, high maneuverability, and stable structure, are particularly well-suited for exploring multi-dimensional data types. However, the design potential of these cubes is underexplored. This study introduces a design space for tangible cubes in MR, focusing on interaction space, visualization space, sizes, and multiplicity. Using spatio-temporal data, we explored the interaction affordances of these cubes in a workshop (N=24). We identified unique interactions like rotating, tapping, and stacking, which are linked to augmented reality (AR) visualization commands. Integrating user-identified interactions, we created a design space for tangible-cube interactions and visualization. A prototype visualizing global health spending with small cubes was developed and evaluated, supporting both individual and combined cube manipulation. This research enhances our grasp of tangible interaction in MR, offering insights for future design and application in diverse data contexts.

Foot-based input can serve as a supplementary or alternative approach to text entry in virtual reality (VR). This work explores the feasibility and design of foot-based techniques that are hands-free. We first conducted a preliminary study to assess foot-based text entry in standing and seated positions with tap and swipe input approaches. The findings showed that foot-based text input was feasible, with the possibility for performance and usability improvements. We then developed three foot-based techniques, including two tap-based techniques (FeetSymTap and FeetAsymTap) and one swipe-based technique (FeetGestureTap), and evaluated their performance via another user study. The results show that the two tap-based techniques supported entry rates of 11.12 WPM and 10.80 WPM, while the swipe-based technique led to 9.16 WPM. Our findings provide a solid foundation for the future design and implementation of foot-based text entry in VR and have the potential to be extended to MR and AR.

Current voice assistants present messages in a predefined format without considering users’ mental states. This paper presents an optimization-based approach to alleviate this issue which adjusts the level of details and speech speed of the voice messages according to the estimated cognitive load of the user. In the first user study (N = 12), we investigated the impact of cognitive load on user performance. The findings reveal significant differences in preferred message formats across five cognitive load levels, substantiating the need for voice message adaptation. We then implemented AdaptiveVoice, an algorithm based on combinatorial optimization to generate adaptive voice messages in real time. In the second user study (N = 30) conducted in a VR-simulated driving environment, we compare AdaptiveVoice with a fixed format baseline, with and without visual guidance on the Heads-up display (HUD). Results indicate that users benefit from AdaptiveVoice with reduced response time and improved driving performance, particularly when it is augmented with HUD.

Sedentary behavior is becoming increasingly prevalent in daily work and study environments. VR exergaming has emerged as a promising solution in these places of work and study. However, private spaces in these environments are not easy, and engaging in VR exergaming in public settings presents its own set of challenges (e.g., safety, social acceptance, isolation, and privacy protection). The recent development of Passthrough functionality in VR headsets allows users to maintain awareness of their surroundings, enhancing safety and convenience. Despite its potential benefits, little is known about how Passthrough could affect user performance and experience and solve the challenges of playing VR exergames in real-world public environments. To our knowledge, this work is the first to conduct a field study in an underground passageway on a university campus to explore the use of Passthrough in a realworld public environment, with a disturbance-free closed room as a baseline. Results indicate that enabling Passthrough in a public environment improves performance without compromising presence. Moreover, Passthrough can increase social acceptance, especially among individuals with higher levels of self-consciousness. These findings highlight Passthrough’s potential to encourage VR exergaming adoption in public environments, with promising implications for overall health and well-being.

Virtual reality (VR) not only allows head-mounted display (HMD) users to immerse themselves in virtual worlds but also to share them with others. When designed correctly, this shared experience can be enjoyable. However, in typical scenarios, HMD users are isolated by their devices, and non-HMD observers lack connection with the virtual world. To address this, our research investigates visually representing observers on both HMD and 2D screens to enhance shared experiences. The study, including five representation conditions, reveals that incorporating observer representation positively impacts both HMD users and observers. For how to design and represent them, our work shows that HMD users prefer methods displaying real-world visuals, while observers exhibit diverse preferences regarding being represented with real or virtual images. We provide design guidelines tailored to both displays, offering valuable insights to enhance co-located shared VR experiences for HMD users and non-HMD observers.

Piloting requires users to control and navigate the aircraft within a designated pathway, with a controller that utilizes two joysticks to control the aircraft. This task is representative of various daily and gaming scenarios, such as controlling the aircraft to capture the photo or navigating an object in a game from the start position to the end via a trajectory. In this work, we explore a model (based on the Steering Law) that predicts the piloting time required in spatial-constrained environments. Thus, two user studies are conducted to help us understand the relationship between path complexity (curvature) and spatial constraints (width and height). According to the results, we propose a model that can achieve $52.6 \%$ and $60.6 \%$ improvement in R-square and the Akaike Information Criterion (AIC), respectively. Next, an additional study was conducted to further verify the performance and efficiency of our proposed model with the change of movement direction and orientation. Our model and experimental results can benefit both game and interface designers of applications that require controlling moving objects along specific trajectories in virtual reality environments.

Recognizing the potential of freehand gestures for interacting with virtual objects in virtual environments, our research introduces a user-defined freehand gesture set of typical referents in virtual reality (VR), focusing on a specific scenario: VR museums. We conducted a comprehensive elicitation study with two experiments to define and refine the gesture set. Meanwhile, we demonstrated an enhanced real-time Wizard of Oz approach that facilitated users’ understanding of referents in VR and their gesture design. Our findings revealed significant improvements in gesture consistency and user agreement through two experiments, with an average agreement score of firstchoice and second-choice advancing from 0.211 and 0.160 to 0.412 and 0.284, respectively. By offering a consistent user-centered gesture set, this work contributes to guiding museum curators toward creating more immersive user experiences in VR museums. The gestures can also be extended to other VR applications that necessitate travel, selection and manipulation, and system control tasks.

With the exponential growth of digital information, ensuring text security, a fundamental component of information security, becomes increasingly paramount. While authentication remains a primary focus for data access control and protection, the rich sensor ecosystem and immersive experiences of virtual reality (VR) environments introduce new privacy risks, particularly with inconspicuous sensors like motion and location sensors. In this context, protecting the security of text entered by users poses a unique challenge. This paper explores the feasibility of enhancing text security by introducing variability in virtual input tools during typing processes. Specifically, we investigate the impact of introducing successive and random intermittent variations to the virtual ray (start point and direction) with controller-based raycasting techniques on text security and typing experience. The results demonstrate that introducing variability in virtual ray effectively protects regular text and passwords. Random intermittent introducing variability balances security and user experience for regular text. These findings provide insights into enhancing text security beyond authentication and defending against the potential risks in VR environments.

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.

Museum visitors are typically advised to follow trajectories planned by curators. Nevertheless, the diverse locomotion techniques available in Virtual Reality (VR) offer various navigation methods that are unattainable within physical museum spaces. Interestingly, these techniques have rarely been explored within museum settings. Our study aims to investigate appropriate navigation methods in VR museums. We first conducted a study in a virtual reconstruction of a local museum with the following navigation methods: a 2D minimap, a World-in-Miniature (WiM) system, and a WiM map. Our results showed that the WiM map with a point-and-select interaction technique outperformed the other two regarding ease of learning, reduced workload, lessened motion sickness, and greater user preferences. Based on the findings, we improved the WiM map and introduced MagicMap. It builds upon the WiM map and translates the curatorial principles of museum visiting into a hierarchical menu layout. Our further evaluation showed that MagicMap supported prolonged engagement in VR museums, enhanced system usability and overall user experience, and reduced users’ perceived workload. Our findings have implications for the future design of navigation systems in VR museums and complex indoor environments.

Virtual reality (VR) offers immense freedom in the design of virtual instructional environments, but little guidance exists on how to capitalise on this freedom. This article reports on a study exploring how audience familiarity influences public speaking anxiety (PSA) and performance in a presentation speaking task in virtuo and in situ. Questionnaire instruments were used to gauge the PSA, motivation, focus, and self-confidence of 10 undergraduate students who each presented in four different audience conditions across VR and real life. Presentations were transcribed to identify features of performance, including utterance fluency, and speaking breadth and depth. Outcomes indicated that an audience of computer-generated agents resulted in less PSA than an audience of photorealistic people familiar to the speakers. Additionally, presenting to an audience of strangers in real life induced the most anxiety, but the performance features of articulation rate, disfluencies, and frequency of silent pauses were significantly improved in this condition. The main contribution of this study is to show that presentations directed at virtual audiences exhibit less fluent speech in non-native speakers than speeches to a real audience.

Healthcare personnel suffer from an increased risk of stress, burnout, and depression due to the challenges of the COVID-19 pandemic. Studies show that interactive smart textiles help people alleviate their emotions. In this research, we investigate how to utilise interactive textiles to help healthcare workers mitigate their negative feelings. We have designed a smart t-shirt that encourages its wearers to perform body movements to enhance their positive emotions, stimulated by vibrotactile and audio feedback mechanisms. We demonstrate our smart t-shirt’s utility by asking healthcare workers (including physicians and nurses) to use it for five consecutive days. Our prototype design supports using it anywhere, including work, home, and other places. We evaluated our smart t-shirt prototype for emotion regulations at work for healthcare workers through an in-situ user study conducted at three hospitals. Results show that using the smart t-shirt positively impacts the healthcare workers’ immediate emotion regulation when they experienced emotion fluctuation and provided a more positive attitude towards their work. We conclude by analysing the potential factors that influence emotions and outline the design space of e-textiles for emotion regulation in real-life use.

As Virtual Reality (VR) applications gain popularity, the need for a secure, usable, and memorable user authentication method becomes crucial. However, security and privacy in such VR applications are often ignored. Current methods are insufficient in preventing man-in-the-room (MITR) attacks, which allow attackers to observe user interactions in VR while remaining invisible, and inputted passwords can easily be stolen. In this study, we propose a dynamic combination of multi-attribute authentication methods for VR, where various 3D objects and their attributes can be created and displayed. Users must select combinations of 3D objects and their attributes provided by our designed principles for identity authentication. We explore the impact of method parameters on security and provide three specific parameter schemes to deploy the practical authentication system. We designed three user studies to evaluate the usability, security, and memorability of our authentication system. The results show that the proposed scheme can effectively resist both shoulder surfing and MITR attacks with unsuccessful attack rates of 100% and 95.83%, respectively. Furthermore, this research provides suggestions to secure VR applications while maintaining usability and enhancing the memorability of the authentication method.

Users’ motion representation in virtual reality (VR) can be modulated visually by introducing a mismatch with their real motion, which can bring benefits to exercise and rehabilitation and has great potential for exergame applications in VR. Users’ experience of control is a critical consideration for user experience in human–computer interaction and should be paid special attention when movement modulation is implemented in VR. However, how movement modulation affects users’ experience of control and motor performance has not been fully investigated in detail. This research included 49 participants and investigated how the experience of control is influenced by reaching movement modulation in two types: the enhancement and reduction modes. Different modulation modes were designed to study their influence on the explicit experience of control in self-ratings and the implicit measured experience of control in intentional binding and electroencephalography. Participants’ movement trajectory, velocity, and completion time were analyzed for motor performance. The results illustrate a significant effect of movement modulation on the users’ motor performance and experience of control in self-ratings and EEG. This study makes a major contribution through a comprehensive analysis of the experience of control with movement modulation and provides important and practical design considerations on movement modulation design in future exercise-based applications with positive controlling experiences in VR.

Museum artifacts are the main way for visitors to experience and learn about cultural heritage. Augmented reality (AR) allows for high interactivity and is increasingly applied in museums to improve tourists’ experience and learning. It also supports the extension of museum experience to outside of the physical museum space, contributing to the visiting trajectory and takeaway experience. In this paper, we present our design of two tangible AR interfaces for cultural artifacts: Postcard AR and CubeMuseum AR, followed by three user studies that evaluate and optimize the design. In Study 1, we conducted a within-subjects study (N = 24) that compares the two AR interfaces with a baseline condition (Leaflet). Our results demonstrate the positive effects of tangible AR interfaces on users’ motivation and engagement in learning cultural heritage. In Study 2, we further explored how to optimize CubeMuseum AR by adopting a user-centered design approach. Through the analysis of expert interviews (N = 7) and an online survey (N = 207), the results specify a series of requirements and design guidelines for tangible AR interfaces to be used as a learning tool and a hybrid gift. Based on the findings, the design of the CubeMuseum AR was optimized and evaluated in Study 3. A between-subjects user study was conducted (N = 32) to compare the optimized design with the initial design. The results verified the positive effects of gamified tangible AR interfaces on users’ motivation, engagement, and performance in learning cultural heritage. We present our design and evaluation results, and discuss the implications of designing tangible AR interfaces for cultural heritage learning and museum gifting.

We investigate how gender-anonymous voice avatars influence women’s performance in online computing group work. Female participants worked with two male confederates. Voices were filtered according to four voice gender anonymity conditions: (1) All unmasked, (2) Male confederates masked, (3) Female participant masked, and (4) All masked. When only male confederates used masked voices (compared to all unmasked), female participants spoke for a longer period of time and scored higher on computing problems. When everyone used masked voices (compared to all unmasked), female participants spoke for a longer period of time, spoke more words, and scored higher on computing problems. Effects were not significant on subjective measures and one behavioral measure. We discuss the implications for virtual interactions between people.

On-body menus present a novel interaction paradigm within Virtual Reality (VR) environments by embedding virtual interfaces directly onto the user’s body. Unlike traditional screen-based interfaces, on-body menus enable users to interact with virtual options or icons visually attached to their physical form. In this paper, We investigated the impact of the creation process on the effectiveness of on-body menus, comparing first-person, third-person, and mirror perspectives. Our first study ( N = 12) revealed that the mirror perspective led to faster creation times and more accurate recall compared to the other two perspectives. To further explore user preferences, we conducted a second study ( N = 18) utilizing a VR system with integrated body tracking. By combining distributions of icons from both studies ( N = 30), we confirmed significant preferences in on-body menu placement based on icon category ( e.g. , Social Media icons were consistently placed on forearms). We also discovered associations between categories, such as Leisure and Social Media icons frequently co-occurring. Our findings highlight the importance of the creation process, uncover user preferences for on-body menu organization, and provide insights to guide the development of intuitive and effective on-body interactions within virtual environments.

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.

VR exergames offer an engaging solution to combat sedentary behavior and promote physical activity. However, challenges emerge when playing these games in shared spaces, particularly due to the presence of bystanders. VR's passthrough functionality enables players to maintain awareness of their surrounding environment while immersed in VR gaming, rendering it a promising solution to improve users' awareness of the environment. This study investigates the passthrough's impact on player performance and experiences in shared spaces, involving an experiment with 24 participants that examines Space (Office vs. Corridor) and Passthrough Function (With vs. Without). Results reveal that Passthrough enhances game performance and environmental awareness while reducing immersion. Players prefer an open area to an enclosed room, whether with or without Passthrough, finding it more socially acceptable. Additionally, Passthrough appears to encourage participation among players with higher self-consciousness, potentially alleviating their concerns about being observed by bystanders. Our findings provide valuable insights for designing VR experiences in shared spaces, underscoring the potential of VR's passthrough to enhance user experiences and promote VR adoption in these environments.

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.

Authentication in digital security relies heavily on text-based passwords, even with other available methods like biometrics and graphical passwords. While virtual reality (VR) keyboards are typically invisible to onlookers, the presence of inconspicuous sensors, including accelerometers, gyroscopes, and barometers, poses a potential risk of unauthorized observation and recording. Traditional defense shoulder-surfing attack methods typically involve breaking apart the Qwerty layout, which destroys the user's inherent familiarity with the layout. This research addresses the need for secure password entry in VR environments while retaining the Qwerty layout. We explore three keyboard-related position alteration strategies to ensure security while mitigating the decline in user experience. These strategies involve moving the entire keyboard, cursor, and keys. Our theoretical study assesses the effectiveness of these strategies against shoulder-surfing attacks. Two user studies, employing ray-based and position-based text entry methods, respectively, evaluate the practical effectiveness of the three strategies in resisting shoulder-surfing attacks, as well as their impact on typing performance and user experience. Our findings demonstrate that the three strategies achieve shoulder-surfing attack resistance comparable to a random layout keyboard. Moreover, compared to a random layout, the two strategies involving the movement of the entire keyboard and the repositioning of keys support faster entry rates and enhanced user experience.

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.

Steering is a fundamental task in interactive Virtual Reality (VR) systems. Prior work has demonstrated that movement direction can significantly influence user behavior in the steering task, and different interactive environments (VEs) can lead to various behavioral patterns, such as tablets and PCs. However, its impact on VR environments remains unexplored. Given the widespread use of steering tasks in VEs, including menu adjustment and object manipulation, this work seeks to understand and model the directional effect with a focus on barehand interaction, which is typical in VEs. This paper presents the results of two studies. The first study was conducted to collect behavioral data with four categories: movement time, average movement speed, success rate, and reenter times. According to the results, we examined the effect of movement direction and built the SθModel. We then empirically evaluated the model through the data collected from the first study. The results proved that our proposed model achieved the best performance across all the metrics (r2 > 0.95), with more than 15% improvement over the original Steering Law in terms of prediction accuracy. Next, we further validated the SθModel by another study with the change of device and steering direction. Consistent with previous assessments, the model continues to exhibit optimal performance in both predicting movement time and speed. Finally, based on the results, we formulated design recommendations for steering tasks in VEs to enhance user experience and interaction efficiency.

The use of Virtual Reality (VR) technology, especially in medical rehabilitation, has expanded to include tactile cues along with visual stimuli. For patients with upper limb hemiplegia, tangible handles with haptic stimuli could improve their ability to perform daily activities. Traditional VR controllers are unsuitable for patient rehabilitation in VR, necessitating the design of specialized tangible handles with integrated tracking devices. Besides, matching tactile stimulation with corresponding virtual visuals could strengthen users' embodiment (i.e., owning and controlling virtual bodies) in VR, which is crucial for patients' training with virtual hands. Haptic stimuli have been shown to amplify the embodiment in VR, whereas the effect of partial tactile stimulation from tangible handles on embodiment remains to be clarified. This research, including three experiments, aims to investigate how partial tactile feedback of tangible handles impacts users' embodiment, and we proposed a design concept called TouchMark for partial tactile stimuli that could help users quickly connect the physical and virtual worlds. To evaluate users' tactile and comfort perceptions when grasping tangible handles in a non-VR setting, various handles with three partial tactile factors were manipulated in Study 1. In Study 2, we explored the effects of partial feedback using three forms of TouchMark on the embodiment of healthy users in VR, with various tangible handles, while Study 3 focused on similar investigations with patients. These handles were utilized to complete virtual food preparation tasks. The tactile and comfort perceptions of tangible handles and users' embodiment were evaluated in this research using questionnaires and interviews. The results indicate that TouchMark with haptic line and ring forms over no stimulation would significantly enhance users' embodiment, especially for patients. The low-cost and innovative TouchMark approach may assist users, particularly those with limited VR experience, in achieving the embodiment and enhancing their virtual interactive experience.

We propose three novel spatial data selection techniques for particle data in VR visualization environments. They are designed to be target- and context-aware and be suitable for a wide range of data features and complex scenarios. Each technique is designed to be adjusted to particular selection intents: the selection of consecutive dense regions, the selection of filament-like structures, and the selection of clusters-with all of them facilitating post-selection threshold adjustment. These techniques allow users to precisely select those regions of space for further exploration-with simple and approximate 3D pointing, brushing, or drawing input-using flexible point- or path-based input and without being limited by 3D occlusions, non-homogeneous feature density, or complex data shapes. These new techniques are evaluated in a controlled experiment and compared with the Baseline method, a region-based 3D painting selection. Our results indicate that our techniques are effective in handling a wide range of scenarios and allow users to select data based on their comprehension of crucial features. Furthermore, we analyze the attributes, requirements, and strategies of our spatial selection methods and compare them with existing state-of-the-art selection methods to handle diverse data features and situations. Based on this analysis we provide guidelines for choosing the most suitable 3D spatial selection techniques based on the interaction environment, the given data characteristics, or the need for interactive post-selection threshold adjustment.

Crowdsourcing in China is a thriving industry. Among its most interesting structures, we find crowdfarms, in which crowdworkers self-organize as small organizations to tackle macrotasks. Little, however, is known as to which practices these crowdfarms use to tackle the macrotasks, and this goes hand in hand with the current practice of the HCI research community to treat all forms of complex crowdsourcing work as practically the same. However, macrotasks differ substantially regarding structure and decomposability. Treating them under one umbrella term - macrotasking - can lead to an imprecise understanding of the workforce involved. We address this gap by examining the work practices of 31 Chinese crowdfarms on the four main macrotask types, namely: modular, interlaced, wicked, and container macrotasks. Our results confirm essential differences in how these nascent crowd organizations address different macrotasks and shed light on what platforms can do to improve the uptake of such work.

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.

Familiarity with audiences plays a significant role in shaping individual performance and experience across various activities in everyday life. This study delves into the impact of familiarity with non-playable character (NPC) audiences on player performance and experience in virtual reality (VR) exergames. By manipulating of NPC appearance (face and body shape) and voice familiarity, we explored their effect on game performance, experience, and exertion. The findings reveal that familiar NPC audiences have a positive impact on performance, creating a more enjoyable gaming experience, and leading players to perceive less exertion. Moreover, individuals with higher levels of self-consciousness exhibit heightened sensitivity to the familiarity with NPC audiences. Our results shed light on the role of familiar NPC audiences in enhancing player experiences and provide insights for designing more engaging and personalized VR exergame environments.

For museums in Virtual Reality (VR), various interaction and manipulation techniques could be employed for users to engage with artefact interactions. This study examined four combinations of interaction (controller-based and hand-tracking) and manipulation (direct and indirect) techniques, assessing user performance and experience with these interaction techniques in a virtual museum environment. We conducted a within-subjects experiment and asked participants to perform a series of transform manipulation tasks using the four techniques. Participants’ task completion time was measured. They also provided feedback on acceptance, learnability, presence, sickness, and fatigue, and gave an overall ranking through post-experiment questionnaires and interviews. The results revealed that controller-based direct manipulation outperformed the other techniques in terms of task performance and user experience, with hand-tracking indirect manipulation being the least efficient and the least preferred option. The study offers insights for future research and development in refining interaction and manipulation techniques and designing more user-friendly VR museum experiences.

Locomotion plays a critical role in user experience in Virtual Reality (VR). This work presents a novel locomotion device, LeanOn, which aims to enhance immersion and feedback experience in VR. Inspired by balance vehicles, LeanOn is a leaning-based locomotion device that allows users to control their location by tilting a board on two balance wheels, with rotation enabled by two buttons near users’ feet. To create a more realistic riding experience, LeanOn is equipped with a terrain vibration system that generates varying levels of vibration based on the roughness of the terrain. We conducted a within-subjects experiment $(\mathrm{N}=24)$ and compared the use of LeanOn and joystick steering in four aspects: cybersickness, spatial presence, feedback experience, and task performance. Participants used LeanOn with and without the vibration system to investigate the necessity of tactile feedback. The results showed that LeanOn significantly improved users’ feedback experience, including autotelic, expressivity, harmony, and immersion, and maintained similar levels of cybersickness and spatial presence, compared to joystick steering. Our work contributes to the field of VR locomotion by validating a leaning-based steering prototype and showing its positive effect on improving users’ feedback experience in VR. We also showed that tactile feedback in locomotion is necessary to further enhance immersion in VR.

The support for multi-focus data exploration is vital in collaborative visualization. In these scenarios, which often involve multiple devices and large displays, users may focus on specific information on their individual screens while also sharing contextual views with others. While many visualization techniques developed for single-user applications can be adapted for use in collaborative settings, little research has been done on how to design adaptive versions of these techniques or how they may impact collaborative tasks involving large datasets. In this work, we perform a comparative study of three collaborative visualization techniques (Zooming, Interactive lenses and Overview+Detail) on large displays in three map-based visualization tasks (Exploration, Comparison and Spatial Memorizing). These three collaborative techniques draw on three different classical visualization techniques in a single-user setting. Our results show that these techniques have different impacts on users’ task performance and preferences. The collaborative Overview+Detail technique benefits users most in supporting Spatial Memorizing. Closely coupled groups prefer collaborative Zooming in Target Exploration. Based on these results, we further discuss the design of collaborative visualization techniques and propose suggestions for adapting classical single-user visualization techniques to a collaborative setting.

It is well documented that exergames are enjoyable to play and can significantly improve older adults’ health and well-being. However, there is limited research on exploring factors affecting these users’ acceptance of such games, especially in virtual reality (VR), a relatively newer technology. This study proposes an extended version of the Technology Acceptance Model (TAM). We use variables from TAM related to older Chinese adults and specific to VR exergames to explore and confirm critical factors that could influence these users’ acceptance of such games in VR. We tested the proposed model with 51 older Chinese adults (aged 65 and above) after playing three commercial VR exergames (Beat Saber, FitXR, Dance Central). Results show that these older adults who are younger and retired and have a higher education, better financial means, and a good health condition have a more positive view of VR exergames. In addition, Perceived Usefulness, Perceived Ease of Use, and Perceived Enjoyment positively affect the intention to play VR exergames. Self-Satisfaction has a positive impact on Perceived Ease of Use and Perceived Usefulness. However, unlike previous studies, our results suggest that Facilitating Conditions have a negative effect on Perceived Ease of Use. Finally, we discuss the theoretical and practical implications of our results.

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.

Virtual reality (VR) technology has progressed rapidly and is used in various domains, particularly games. Simulator sickness (SS) still represents a significant problem for its wider adoption. The most common way to detect SS is using the simulator sickness questionnaire (SSQ). SSQ is a subjective measurement and is inadequate for real-time applications such as VR games. This research aims to develop a model to predict SS in real time using in-game characters’ movement and users’ eye motion data during gameplay in VR games. To achieve this, we designed an experiment to collect such data with three types of games. We trained a long short-term memory neural network with the eye-tracking and character movement data to predict SS. Our model can predict SS in real time with an accuracy of 83.4% for players who suffer from severe sensitivity to SS. Our results indicate that, in VR games, our model is an accurate and efficient method to predict SS in real time.

Virtual reality (VR) has emerged as a powerful tool for rehabilitation. Many effective VR applications have been developed to support motor rehabilitation of people affected by motor issues. Movement reproduction, which transfers users' movements from the physical world to the virtual environment, is commonly used in VR rehabilitation applications. Three major components are required for movement reproduction in VR: (1) movement input, (2) movement representation, and (3) movement modulation. Until now, movement reproduction in virtual rehabilitation has not yet been systematically studied. This article aims to provide a state-of-the-art review on this subject by focusing on existing literature on immersive motor rehabilitation using VR. In this review, we provided in-depth discussions on the rehabilitation goals and outcomes, technology issues behind virtual rehabilitation, and user experience regarding movement reproduction. Similarly, we present good practices and highlight challenges and opportunities that can form constructive suggestions for the design and development of fit-for-purpose VR rehabilitation applications and can help frame future research directions for this emerging area that combines VR and health.

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.

We present EdgeSelect, a linear target selection interaction technique that utilizes a small portion of the smartwatch display, explicitly designed to mitigate the ‘fat finger’ and screen occlusion problems, two of the most common and well-known challenges when interacting with small displays. To design our technique, we first conducted a user study to answer which segments of the smartwatch display have the least screen occlusion while users are interacting with it. We use results from the first experiment to introduce EdgeSelect, a three-layer non-linear interaction technique, which can be used to interact with multiple co-adjacent graphs on the smartwatch by using a region that is the least prone to finger occlusion. In a second experiment, we explore the density limits of the targets possible with EdgeSelect. Finally, we demonstrate the generalizability of EdgeSelect to interact with various types of content.

Materials play an essential role in product design and affect many design aspects. Materials libraries are built by universities to provide resources and inspire design concept generation and decision-making. Augmented reality (AR) is a technology overlaying digital content onto the physical world and brings a new perspective on material library through increased engagement and interactivity. This work-in-progress paper aims to enhance materials education and foster disciplinary communication by establishing an AR materials library. The proposed library will contribute to design and engineering education by serving as a practical platform with material resources and a novel tool engaged in learning.

Hand-based interaction, such as using a handheld controller or making hand gestures, has been widely adopted as the primary method for interacting with both virtual reality (VR) and augmented reality (AR) head-mounted displays (HMDs). In contrast, hands-free interaction avoids the need for users’ hands and although it can afford additional benefits, there has been limited research in exploring and evaluating hands-free techniques for these HMDs. As VR HMDs become ubiquitous, people will need to do text editing, which requires selecting text segments. Similar to hands-free interaction, text selection is underexplored. This research focuses on both, text selection via hands-free interaction. Our exploration involves a user study with 24 participants to investigate the performance, user experience, and workload of three hands-free selection mechanisms (Dwell, Blink, Voice) to complement head-based pointing. Results indicate that Blink outperforms Dwell and Voice in completion time. Users’ subjective feedback also shows that Blink is the preferred technique for text selection. This work is the first to explore handsfree interaction for text selection in VR HMDs. Our results provide a solid platform for further research in this important area.

Text selection is an essential activity in interactive systems, including virtual reality (VR) head-mounted displays (HMDs). It is useful for: sharing information across apps or platforms, highlighting and making notes while reading articles, and text editing tasks. Despite its usefulness, the space of text selection interaction is underexplored in VR HMDs. In this research, we performed a user study with 24 participants to investigate the performance and user preference of six text selection techniques (Controller+Dwell, Controller+Click, Head+Dwell, Head+Click, Hand+Dwell, Hand+Pinch). Results reveal that Head+Click is ranked first since it has excellent speedaccuracy performance (2nd fastest task completion speed with 3rd lowest total error rate), provides the best user experience, and produces a very low workload—followed by Controller+Click, which has the fastest speed and comparable experience with Head+Click, but much higher total error rate. Other methods can also be useful depending on the goals of the system or the users. As a first systematic evaluation of pointing $\times$ selection techniques for text selection in VR, the results of this work provide a strong foundation for further research in this area of growing importance to the future of VR to help it become a more ubiquitous and pervasive platform.

Textile interfaces are of interest to ubiquitous computing as they are easy to carry and manipulate. However, interesting questions remain about what type of natural gestures people make when interacting with textile interfaces and their emotional response to this interaction. We introduce GesFabri, a set of five interactive textile interfaces with distinct textures, created to investigate the intuitive interaction gestures and accompanied the emotional experience. This research sought to (1) design textile interfaces with intuitive gesture affordance, (2) explore the emotional effects of the developed gesture-based interfaces under four feedback modes (touch-only, visual feedback, audio feedback, multisensory feedback). The experimental results verify our hypotheses that (1) textile texture could provide natural gesture affordances; (2) the GesFabri interfaces' feedback mode was the main factor in the differences of emotional valence, arousal, GSR; and (3) both gesture-based interaction on textiles and the feedback mode had an impact on user emotions. These results highlight the gesture affordances of the e-textile interfaces and contribute to a better understanding of the user experience when interacting with gesture-based textile interfaces.

Task-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.

Uncertainty is widely acknowledged as an engaging gameplay element but rarely used in exergames. In this research, we explore the role of uncertainty in exergames and introduce three uncertain elements (false-attacks, misses, and critical hits) to an exergame. We conducted a study under two conditions (uncertain and certain), with two display types (virtual reality and large display) and across young and middle-aged adults to measure their effect on game performance, experience, and exertion. Results show that (1) our designed uncertain elements are instrumental in increasing exertion levels; (2) when playing a motion-based first-person perspective exergame, virtual reality can improve performance, while maintaining the same motion sickness level as a large display; and (3) exergames for middle-aged adults should be designed with age-related declines in mind, similar to designing for elderly adults. We also framed two design guidelines for exergames that have similar features to the game used in this research.

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.

In virtual reality (VR) games, playability and immersion levels are important because they affect gameplay, enjoyment, and performance. However, they can be adversely affected by VR sickness (VRS) symptoms. VRS can be minimized by manipulating users' perception of the virtual environment via the head-mounted display (HMD). One extreme example is the Teleport mitigation technique, which lets users navigate discretely, skipping sections of the virtual space. Other techniques are less extreme but still rely on controlling what and how much users see via the HMD. This research examines the effect on players' performance and gameplay of these mitigation techniques in fast-paced VR games. Our focus is on two types of visual reduction techniques. This study aims to identify specifically the trade-offs these techniques have in a first-person shooter game regarding immersion, performance, and VRS. The main contributions in this paper are (1) a deeper understanding of one of the most popular techniques (Teleport) when it comes to gameplay; (2) the replication and validation of a novel VRS mitigation technique based on visual reduction; and (3) a comparison of their effect on players' performance and gameplay.

Randomness is an important factor in games, so much so that some games rely almost purely on it for its outcomes and increase players' engagement with them. However, randomness can affect the game experience depending on when it occurs in a game, altering the chances of planning for a player. In this paper, we refer to it as “input-output randomness”. Input-output randomness is a cornerstone of collectable card games like Hearthstone, in which cards are drawn randomly (input randomness) and have random effects when played (output randomness). While the topic might have been commonly discussed by game designers and be present in many games, few empirical studies have been performed to evaluate the effects of these different kinds of randomness on the players' satisfaction. This research investigates the effects of input-output randomness on collectable card games across four input-output randomness conditions. We have developed our own collectable card game and experimented with the different kinds of randomness with the game. Our results suggest that input randomness can significantly impact game satisfaction negatively. Overall, our results present helpful considerations on how and when to apply randomness in game design when aiming for players' satisfaction.

With rapid advances in virtual reality (VR) technology, the use of haptics has become important to allow users to feel the physical properties of virtual objects. Current research has focused mainly on either weight variation or changing the center of gravity, which limits the simulation potential and may affect the feeling of immersion. This research explores the design and development of a device that can simulate both weight and center of gravity using low-cost components. Through an iterative design process and continuous testing with users, we arrived at a final prototype, FluidWeight, a device that can be attached to a typical VR handheld controller. FluidWeight uses fluid, which is transported from a central storage to a receptacle attached to the controller. A final experiment shows that users enjoyed using it because it could help increase the sense of realism in VR applications.

Identifying cybersickness in virtual reality (VR) applications such as games in a fast, precise, non-intrusive, and non-disruptive way remains challenging. Several factors can cause cybersickness, and their identification will help find its origins and prevent or minimize it. One such factor is virtual movement. Movement, whether physical or virtual, can be represented in different forms. One way to represent and store it is with a temporally annotated point sequence. Because a sequence is memory-consuming, it is often preferable to save it in a compressed form. Compression allows redundant data to be eliminated while still preserving changes in speed and direction. Since changes in direction and velocity in VR can be associated with cybersickness, changes in compression rate can likely indicate changes in cybersickness levels. In this research, we explore whether quantifying changes in virtual movement can be used to estimate variation in cybersickness levels of VR users. We investigate the correlation between changes in the compression rate of movement data in two VR games with changes in players’ cybersickness levels captured during gameplay. Our results show (1) a clear correlation between changes in compression rate and cybersickness, and (2) that a machine learning approach can be used to identify these changes. Finally, results from a second experiment show that our approach is feasible for cybersickness inference in games and other VR applications that involve movement.

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.

Virtual reality (VR) head-mounted displays (HMD) have recently been used to provide an immersive, first-person vision/view in real-time for manipulating remotely-controlled unmanned ground vehicles (UGV). The teleoperation of UGV can be challenging for operators when it is done in real time. One big challenge is for operators to perceive quickly and rapidly the distance of objects that are around the UGV while it is moving. In this research, we explore the use of monoscopic and stereoscopic views and display types (immersive and non-immersive VR) for operating vehicles remotely. We conducted two user studies to explore their feasibility and advantages. Results show a significantly better performance when using an immersive display with stereoscopic view for dynamic, real-time navigation tasks that require avoiding both moving and static obstacles. The use of stereoscopic view in an immersive display in particular improved user performance and led to better usability.

Text entry is an important and frequent task in interactive devices including augmented reality head-mounted displays (AR HMDs). In current AR HMDs, there are still two main open challenges to overcome for efficient and usable text entry: arm fatigue due to mid-air input and visual occlusion because of their small see-through displays. To address these challenges, we present iText, a technique for AR HMDs that is hands-free and is based on an imaginary (invisible) keyboard. We first show that it is feasible and practical to use an imaginary keyboard on AR HMDs. Then, we evaluated its performance and usability with three hands-free selection mechanisms: eye blinks (E-Type), dwell (D-Type), and swipe gestures (G-Type). Our results show that users could achieve an average text entry speed of 11.95, 9.03 and 9.84 words per minutes (WPM) with E-Type, D-Type, and G-Type, respectively. Given that iText with E-Type outperformed the other two selection mechanisms in text entry rate and subjective feedback, we ran a third, 5-day study. Our results show that iText with E-Type can achieve an average text entry rate of 13.76 WPM with a mean word error rate of 1.5%. In short, iText can enable efficient eyes-free text entry and can be useful for various application scenarios in AR HMDs.

Text entry is a common activity in virtual reality (VR) systems. There is a limited number of available hands-free techniques, which allow users to carry out text entry when users’ hands are busy such as holding items or hand-based devices are not available. The most used hands-free text entry technique is DwellType, where a user selects a letter by dwelling over it for a specific period. However, its performance is limited due to the fixed dwell time for each character selection. In this paper, we explore two other hands-free text entry mechanisms in VR: BlinkType and NeckType, which leverage users’ eye blinks and neck’s forward and backward movements to select letters. With a user study, we compare the performance of the two techniques with DwellType. Results show that users can achieve an average text entry rate of 13.47, 11.18 and 11.65 words per minute with BlinkType, NeckType, and DwellType, respectively. Users’ subjective feedback shows BlinkType as the preferred technique for text entry in VR.

The amount of interest in Virtual Reality (VR) research has significantly increased over the past few years, both in academia and industry. The release of commercial VR Head-Mounted Displays (HMDs) has been a major contributing factor. However, there is still much to be learned, especially how views and input techniques, as well as their interaction, affect the VR experience. There is little work done on First-Person Shooter (FPS) games in VR, and those few studies have focused on a single aspect of VR FPS. They either focused on the view, e.g., comparing VR to a typical 2D display or on the controller types. To the best of our knowledge, there are no studies investigating variations of 2D/3D views in HMDs, controller types, and their interactions. As such, it is challenging to distinguish findings related to the controller type from those related to the view. If a study does not control for the input method and finds that 2D displays lead to higher performance than VR, we cannot generalize the results because of the confounding variables. To understand their interaction, we propose to analyze in more depth, whether it is the view (2D vs. 3D) or the way it is controlled that gives the platforms their respective advantages. To study the effects of the 2D/3D views, we created a 2D visual technique, PlaneFrame, that was applied inside the VR headset. Our results show that the controller type can have a significant positive impact on performance, immersion, and simulator sickness when associated with a 2D view. They further our understanding of the interactions that controllers and views have and demonstrate that comparisons are highly dependent on how both factors go together. Further, through a series of three experiments, we developed a technique that can lead to a substantial performance, a good level of immersion, and can minimize the level of simulator sickness.

Mid-air hand interaction has long been proposed as a ‘natural’ input method for Augmented Reality (AR) systems. Current AR Head-Mounted Displays (HMDs) have a limited area for hand-based interactions. Because of this, users may easily move their hand(s) outside this tracked area during interaction, especially in dynamic tasks (e.g., when translating an object). Compared to common midair interaction issues, such as gesture recognition, arm/hand fatigue, and unnatural ways of interacting with virtual objects (e.g., selecting a distant object), boundary awareness issues in AR devices have received little attention. In this research, we explore visual techniques for boundary awareness in AR HMDs, focusing on object translation tasks. Through a systematic formative study, we first identify the challenges that users might face when interacting with AR HMDs without any boundary awareness information (i.e., how current systems work). Based on the findings, we then propose four methods (i.e., static surfaces, dynamic surface(s), static coordinated lines, and dynamic coordinate line(s)) and evaluate them against the benchmark (i.e., baseline condition without boundary awareness) to make users aware of the tracked interaction area. Our results show that visual methods for boundary awareness can help with dynamic mid-air hand interactions in AR HMDs, but their effectiveness and application are user-dependent.

Despite the growing interest in crowdsourcing, this new labor model has recently received severe criticism. The most important point of this criticism is that crowdworkers are often underpaid and overworked. This severely affects job satisfaction and productivity. Although there is a growing body of evidence exploring the work experiences of crowdworkers in various countries, there have been a very limited number of studies to the best of our knowledge exploring the work experiences of Chinese crowdworkers. In this paper we aim to address this gap. Based on a framework of well-established approaches, namely the Job Demands-Resources model, the Work Design Questionnaire, the Oldenburg Burnout Inventory, the Utrecht Work Engagement Scale, and the Organizational Commitment Questionnaire, we systematically study the work experiences of 289 crowdworkers who work for ZBJ.com - the most popular Chinese crowdsourcing platform. Our study examines these crowdworker experiences along four dimensions: (1) crowdsourcing job demands, (2) job resources available to the workers, (3) crowdwork experiences, and (4) platform commitment. Our results indicate significant differences across the four dimensions based on crowdworkers' gender, education, income, job nature, and health condition. Further, they illustrate that different crowdworkers have different needs and threshold of demands and resources and that this plays a significant role in terms of moderating the crowdwork experience and platform commitment. Overall, our study sheds light to the work experiences of the Chinese crowdworkers and at the same time contributes to furthering understandings related to the work experiences of crowdworkers.

Expressions of territoriality have been positioned as one of the main reasons users alter their behaviors and perceptions of spatiality and sociality while engaging with location-based social networks (LBSN). Despite the potential for this interplay to further our understanding of LBSN usage in the context of identity, very little work has actually been done toward this. Addressing this gap in the literature is one of the chief aims of the article. Drawing on an original 6-week study with 42 participants utilizing a bespoke LBSN entitled “GeoMoments,” our research explores the following: (1) the way that territoriality is linked to self-identity; and (2) how this interplay affects the interactions between users as well as the environments they inhabit. Our findings suggest that participants affirmed their self-identity by selectively posting and claiming ownership of their neighborhood through the LBSN. Here, the locative decisions are made related to risk, hierarchies, and the users’ relationship to the area. This practice then led participants to discover and interact with the digital information overlaying their physical environments in a playful manner. These interactions demonstrate the perceived power structures that are facilitated by identity claims over a virtual area. In the main, our results reaffirm that territoriality is a central concept in understanding LBSN use, while also drawing attention to the temporality involved in user-to-user and user-to-place interactions pertaining to physical place mediated by LBSN.

This research explores the design and evaluation of visualization techniques of targets that reside outside of users' view and/or are occluded by other elements within a virtual reality environment (VE). We first compare four techniques (3DWedge, 3DArrow, 3DMinimap, and Radar) that use different types of visual elements to provide direction and distance information of targets. To give structure to their evaluation, we also develop a framework of four tasks (one for direction and three for distance) and their assessment criteria. The results of the first study show that 3DWedge is the best-performing and most usable technique. However, all techniques, including 3DWedge, have poor performance in dense scenarios with a large number of targets. To improve support in dense scenarios, a fifth technique, 3DWedge+, is developed by using 3DWedge as its foundation and including additional visual elements that are derived from the other three techniques which are shown to be useful. A second study is conducted to evaluate the performance of 3DWedge+ in relation to the other techniques. The results show that both 3DWedge and 3DWedge+ are significantly better in distinguishing user-to-target distance and that 3DWedge+ is particularly suitable for dense scenarios. Based on these results, we provide a set of recommendations for the design of visualization techniques of off-screen and occluded targets in 3D VE.

We present DMove, directional motion-based interaction for Augmented Reality (AR) Head-Mounted Displays (HMDs) that is both hands- and device-free. It uses directional walk-ing as a way to interact with virtual objects. To use DMove, a user needs to perform directional motions such as mov-ing one foot forward or backward. In this research, we first investigate the recognition accuracy of the motion direc-tions of our method and the social acceptance of this type of interactions together with users' comfort rating for each direction. We then optimize its design and conduct a sec-ond study to compare DMove in task performance and user preferences (workload, motion sickness, user experience), with two approaches-Hand interaction (Meta 2-like) and Head+Hand interaction (HoloLens-like) for menu selection tasks. Based on the results of these two studies, we provide a set of guidelines for DMove and further demonstrate two applications that utilize directional motions.

In this paper we present a comparative study of visual instructions in Immersive Virtual Reality (IVR), i.e., annotation (ANN) that employs 3D texts and objects for instructions and virtual tutor (TUT) that demonstrates a task with a 3D character. The comparison is based on three tasks, maze escape (ME), stretching exercise (SE), and crane manipulation (CM), defined by the types of a unit instruction. We conducted an automated evaluation of user's memory recall performances (recall time, accuracy, and error) by mapping a sequence of user's behaviors and events as a string. Results revealed that ANN group showed significantly more accurate performance (1.3 times) in ME and time performance (1.64 times) in SE than TUT group, while no statistical main difference was found in CM. Interestingly, although ANN showed statistically shorter execution time, the recalling time pattern of TUT group showed a steep convergence after initial trial. The results can be used in the field in terms of informing designers of IVR on what types of visual instruction are best for different task purpose.

Augmented reality (AR) is on the rise with consumer-level head-mounted displays (HMDs) becoming available in recent years. Text entry is an essential activity for AR systems, but it is still relatively underexplored. Although it is possible to use a physical keyboard to enter text in AR systems, it is not the most optimal and ideal way because it confines the uses to a stationary position and within indoor environments. Instead, a virtual keyboard seems more suitable. Text entry via virtual keyboards requires a pointing method and a selection mechanism. Although there exist various combinations of pointing+selection mechanisms, it is not well understood how well suited each combination is to support fast text entry speed with low error rates and positive usability (regarding workload, user experience, motion sickness, and immersion). In this research, we perform an empirical study to investigate user preference and text entry performance of four pointing methods (Controller, Head, Hand, and Hybrid) in combination with two input mechanisms (Swype and Tap). Our research represents a first systematic investigation of these eight possible combinations. Our results show that Controller outperforms all the other device-free methods in both text entry performance and user experience. However, device-free pointing methods can be usable depending on task requirements and users' preferences and physical condition.

Head-based interactions are very handy for virtual reality (VR) head-worn display (HWD) systems. A useful head-based interaction technique could help users to interact with VR environments in a hands-free manner (i.e., without the need of a hand-held de-vice). Moreover, it can sometimes be seamlessly integrated with other input modalities to provide richer interaction possibilities. This paper explores the potential of a new approach that we call DepthMove to allow interactions that are based on head motions along the depth dimension. With DepthMove, a user can interact with a VR system proactively by moving the head perpendicular to the VR HWD forward or backward. We use two user studies to investigate, model, and optimize DepthMove by taking into con-sideration user performance, subjective response, and social ac-ceptability. The results allow us to determine the optimal and comfortable DepthMove range. We also distill recommendations that can be used to guide the design interfaces that use DepthMove for efficient and accurate interaction in VR HWD systems. A third study is conducted to demonstrate the usefulness of DepthMove relative to other techniques in four application scenarios.

Text entry is a common activity in virtual reality (VR) systems. However, there is a limited number of approaches available for mobile VR systems, where it might be inconvenient for users to carry an input device. We propose a novel hands-free text entry technique we call DepthText which leverages the acceleration sensing abilities of built-in IMU sensors of mobile VR systems. Users are able to enter text by moving their head forward. The results of a 5-day study indicate that users can achieve an average of 10.76 words per minute (wpm) on the last day with low errors. This performance is comparable to the dwell-based technique which is the most common way of entering text that is hands-free. One advantage of DepthText over the dwell-based technique is that users can have more control of the pace of selecting characters, rather than being pushed by a pre-set dwell time.

Hands-free interactions are very handy for virtual reality (VR) head-worn display (HWD) systems because they allow users to interact with VR environments without the need for a hand-held device. This paper explores the potential of a new approach that we call DepthMove to allow hands-free interactions that are based on head motions towards the depth dimension. With DepthMove, a user can interact in a VR system proactively by moving towards the depth dimension with an HWD. We present the concept and implementation of DepthMove in VR HWD systems and demonstrate its potential applications. We further discuss the advantages and limitations of using DepthMove.

Understanding the endpoint distribution of pointing selection tasks can reveal the underlying patterns on how users tend to acquire a target, which is one of the most essential and pervasive tasks in interactive systems. It could further aid designers to create new graphical user interfaces and interaction techniques that are optimized for accuracy, efficiency, and ease of use. Previous research has explored the modeling of endpoint distribution outside of virtual reality (VR) systems that have shown to be useful in predicting selection accuracy and guide the design of new interactive techniques. This work aims at developing an endpoint distribution of selection tasks for VR systems which has resulted in EDModel , a novel model that can be used to predict endpoint distribution of pointing selection tasks in VR environments. The development of EDModel is based on two users studies that have explored how factors such as target size, movement amplitude, and target depth affect the endpoint distribution. The model is built from the collected data and its generalizability is subsequently tested in complex scenarios with more relaxed conditions. Three applications of EDModel inspired by previous research are evaluated to show the broad applicability and usefulness of the model: correcting the bias in Fitts's law, predicting selection accuracy, and enhancing pointing selection techniques. Overall, EDModel can achieve high prediction accuracy and can be adapted to different types of applications in VR.

In this paper, we present a case for text entry using a circular keyboard layout for mobile head-mounted displays (HMDs) that is dwell-free and does not require users to hold a dedicated input device for letter selection. To support the case, we have implemented RingText whose design is based on a circular layout with two concentric circles. The outer circle is subdivided into regions containing letters. Selection is made by using a virtual cursor controlled by the user's head movements-entering a letter region triggers a selection and moving back into the inner circle resets the selection. The design of RingText follows an iterative process, where we initially conduct one first study to investigate the optimal number of letters per region, inner circle size, and alphabet starting location. We then optimize its design by selecting the most suitable features from the first study: one letter per region, narrowing the trigger area to lower error rates, and creating candidate regions that incorporate two suggested words to appear next to the current letter region (close to the cursor) using a dynamic (rather than fixed) approach. Our second study compares text entry performance of RingText with four other hands-free techniques and the results show that RingText outperforms them. Finally, we run a third study lasting four consecutive days with 10 participants (5 novice users and 5 expert users) doing two daily sessions and the results show that RingText is quite efficient and yields a low error rate. At the end of the eighth session, the novice users can achieve a text entry speed of 11.30 WPM after 60 minutes of training while the expert (more experienced) users can reach an average text entry speed of 13.24 WPM after 90 minutes of training.

Presents corrections to author information for the paper, “RingText: Dwell-Free and Hands-Free Text Entry for Mobile Head-Mounted Displays Using Head Motions,” (Xu, W., et al), IEEE Trans. Vis. Comput. Graph., vol. 25, no. 5, pp. 1991–2001, May 2019.

Interactive visualizations are external cognitive artifacts aimed at supporting users' exploratory and sense-making activities. In recent years, there has been an explosion of commercial virtual reality (VR) head-mounted displays (HMD). These VR devices are meant to offer high levels of engagement and improve users' analytical exploration of the displayed content. However, given their rapid market introduction, the possible influences and usefulness that VR could bring in terms of supporting users' exploration with interactive visualizations remain largely underexplored. We attempt to fill this gap and provide results of an empirical study of an interactive visualization tool that we have developed for a VR HMD system. This tool is aimed at facilitating exploratory and analytical reasoning activities with 3D shapes and their transformational processes. Overall, the results show that the tool is supportive of users' exploratory and analytical activities based on the significant improvement in their post-experiment test scores (when compared to their pre-experiment ones) and their engagement level measured via a user engagement questionnaire and participants' comments. The results shed a positive light on the use of visualizations in VR environments and can inform the design of these tools of domains beyond 3D transformational geometry.

Abstract This research explores the suitability and effectiveness of two relatively new types of input device for navigating 3D virtual environments. These are infrared motion detection, like the Leap Motion tracker, and electromyographic gesture recognition, like the Myo Armband. Despite the introduction of a variety of new input devices intended to provide a more natural interaction experience, navigation within 3D virtual environments is still normally done on more traditional control devices such as game controllers or the keyboard–mouse combination. This study investigates the potential of new devices to support navigation in 3D environments through an experiment conducted with 27 participants using three different types of input devices to play a ball‐balancing maze‐like game. The input devices tested are a standard game controller, a Leap Motion tracker for infrared motion detection, and the Myo Armband for electromyographic gesture recognition. Results demonstrated the real potential of both types of device to support navigation interaction within 3D environments.

Abstract Many virtual reality (VR) games are based on a first‐person perspective (1PP). There are, however, advantages in using another perspective, such as the third‐person perspective (3PP). Although there has been some research evaluating the effect of 1PP and 3PP in gameplay experiences, it is largely unexplored for VR games played via the new generation of commercial head‐mounted display systems, such as the Oculus Rift. In this research we want to shed some light on the relationship between the different perspectives, when games are played using head‐mounted display VR, and simulator sickness, enjoyment, and presence. To do so, we perform an experiment using two different perspectives (1PP and 3PP) and displays (VR and a conventional display) with a popular game. Our findings indicate that 3PP‐VR is less likely to make people have simulator sickness when compared with 1PP‐VR. However, the former is not perceived as immersive, but this might not be a problem because our data also show that presence is not mandatory for enjoyment. Also, the data suggest that there is no clear preference between 1PP‐VR and 3PP‐VR for gameplay.

We present PizzaText, a circular keyboard layout technique for text entry in virtual reality (VR) environments that uses the dual thumbsticks of a hand-held game controller. Text entry is a common activity in VR environments but remains challenging with existing techniques and keyboard layouts that is largely based on QWERTY. Our technique makes text entry simple, easy, and efficient, even for novice users. The technique uses a hand-held controller because it is still an important input device for users to interact with VR environments. To allow rapid search of characters, PizzaText divides a circle into slices and each slice contains 4 characters. To enable fast selection, the user uses the right thumbstick for traversing the slices, and the left thumbstick for choosing the letters. The design of PizzaText is based on three criteria: efficiency, learnability, and ease-of-use. In our first study, six potential layouts are considered and evaluated. The results lead to a design with 7 slices and 4 letters per slice. The final design is evaluated in a five-day study with 10 participants. The results show that novice users can achieve an average of 8.59 Words per Minute (WPM), while expert users are able to reach 15.85 WPM, with just two hours of training.

Adversarial examples are augmented data points generated by imperceptible perturbation of input samples. They have recently drawn much attention with the machine learning and data mining community. Being difficult to distinguish from real examples, such adversarial examples could change the prediction of many of the best learning models including the state-of-the-art deep learning models. Recent attempts have been made to build robust models that take into account adversarial examples. However, these methods can either lead to performance drops or lack mathematical motivations. In this paper, we propose a unified framework to build robust machine learning models against adversarial examples. More specifically, using the unified framework, we develop a family of gradient regularization methods that effectively penalize the gradient of loss function w.r.t. inputs. Our proposed framework is appealing in that it offers a unified view to deal with adversarial examples. It incorporates another recently-proposed perturbation based approach as a special case. In addition, we present some visual effects that reveals semantic meaning in those perturbations, and thus support our regularization method and provide another explanation for generalizability of adversarial examples. By applying this technique to Maxout networks, we conduct a series of experiments and achieve encouraging results on two benchmark datasets. In particular, we attain the best accuracy on MNIST data (without data augmentation) and competitive performance on CIFAR-10 data.

Tabletop systems provide a versatile space for collaboration, yet, in many cases, are limited by the inability to differentiate the interactions of simultaneous users. We present See Me, See You, a lightweight approach for discriminating user touches on a vision-based tabletop. We contribute a valuable characterization of finger orientation distributions of tabletop users. We exploit this biometric trait with a machine learning approach to allow the system to predict the correct position of users as they touch the surface. We achieve accuracies as high as 98% in simple situations and above 92% in more challenging conditions, such as two-handed tasks. We show high acceptance from users, who can self-correct prediction errors without significant costs. See Me, See You is a viable solution for providing simple yet effective support for multi-user application features on tabletops.

Observational studies indicate that most people use one hand to interact with their mobile devices. Interaction on the back-of-devices (BoD) has been proposed to enhance one-handed input for various tasks, including selection and gesturing. However, we do not possess a good understanding of some fundamental issues related to one-handed BoD input. In this paper, we attempt to fill this gap by conducting three studies. The first study explores suitable selection techniques; the second study investigates the performance and suitability of the two main modes of cursor movement: Relative and Absolute; and the last study examines solutions to the problem of reaching the lower part of the device. Our results indicate that for BoD interaction, relative input is more efficient and accurate for cursor positioning and target selection than absolute input. Based on these findings provide guidelines for designing BoD interactions for mobile devices.

Devices with small viewports (e.g., smartphones or GPS) result in interfaces where objects of interest can easily reside outside the view, into off-screen space. Researchers have addressed this challenge and have proposed visual cues to assist users in perceptually locating off-screen objects. However, little attention has been placed on methods for selecting the objects. Current designs of off-screen cues can result in overlaps that can make it difficult to use the cues as handles through which users can select the off-screen objects they represent. In this paper, we present EdgeSplit, a technique that facilitates both the visualization and selection of off-screen objects on small devices. EdgeSplit exploits the space around the device's borders to display proxies of off-screen objects and then partitions the border regions to allow for non-overlapping areas that make selection of objects easier. We present an effective algorithm that provides such partitioning and demonstrate the effectiveness of EdgeSplit for selecting off-screen objects.

Complex visualization spaces are not easy to explore. This is especially true of exploring 4D mathematical structures due to occlusion and visual clutter. In this paper, we present preliminary results involving a usability study of two strategies for designing interaction strategies, namely, externalization and composite interactions, to aid in the exploration of 4D mathematical structures. Study results show the potential benefits of these two strategies for exploring complex mathematical structures, in particular, and other complex visualization spaces, in general.

Journal Article Designing interfaces that support formation of cognitive maps of transitional processes: an empirical study Get access Kamran Sedig, Kamran Sedig ⁎ a Department of Computer Science and Faculty of Information and Media Studies, The University of Western Ontario, Middlesex College, London, ON N6A 5B7, Canada ⁎ Tel.: +1 519 661 2111x86612; fax: +1 519 661 3506. E-mail address:[email protected] (K. Sedig). Search for other works by this author on: Oxford Academic Google Scholar Sonja Rowhani, Sonja Rowhani b Department of Computer Science, The University of Western Ontario, Middlesex College, London, ON N6A 5B7, Canada Search for other works by this author on: Oxford Academic Google Scholar Hai-Ning Liang Hai-Ning Liang b Department of Computer Science, The University of Western Ontario, Middlesex College, London, ON N6A 5B7, Canada Search for other works by this author on: Oxford Academic Google Scholar Interacting with Computers, Volume 17, Issue 4, July 2005, Pages 419–452, https://doi.org/10.1016/j.intcom.2005.02.002 Published: 27 April 2005 Article history Received: 09 March 2004 Revision received: 15 October 2004 Accepted: 21 February 2005 Published: 27 April 2005