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.

Interacting with multiple objects simultaneously makes us fast. A pre-step to this interaction is to select the objects, i.e., multi-object selection, which is enabled through two steps: (1) toggling multi-selection mode — mode-switching — and then (2) selecting all the intended objects — subselection. In extended reality (XR), each step can be performed with the eyes, hands, and voice. To examine how design choices affect user performance, we evaluated four mode-switching (SemiPinch, FullPinch, DoublePinch, and Voice) and three subselection techniques (Gaze+Dwell, Gaze+Pinch, and Gaze+Voice) in a user study. Results revealed that while DoublePinch paired with Gaze+Pinch yielded the highest overall performance, SemiPinch achieved the lowest performance. Although Voice-based mode-switching showed benefits, Gaze+Voice subselection was less favored, as the required repetitive vocal commands were perceived as tedious. Overall, these findings provide empirical insights and inform design recommendations for multi-selection techniques in XR.

Disambiguating distal target selection in dense and occluded virtual environments has been a challenge for Virtual Reality (VR) interaction design. While raycasting is a widely used interaction technique for selecting distant objects, it defaults to the first intersected target, forcing users into disambiguation phases, which can disrupt presence, increase cognitive load, and slow interaction. We introduce VoiceRay, a voice-based target selection that allows users to specify the ordinal position of the intended target along the ray (e.g., “second object”) without altering the scene or requiring additional inputs from the user. In a study with 24 participants, VoiceRay was compared against five existing techniques: AlphaCursor, LassoGrid, RayCursor, BubbleRay, and Raycasting. Results showed that VoiceRay significantly decreased selection time, maintained presence, increased usability, and reduced cognitive load. These findings demonstrate that voice-based interaction offers an effective, easy-to-use alternative for resolving 3D selection ambiguity in dense and occluded VR environments.

Gesture interaction is standard in modern extended reality head-mounted displays, e.g., Microsoft HoloLens 2 and Apple Vision Pro. These gestures come from multiple sources, such as elicitation studies, the application designer, or an expert. However, it is unclear if the source of the gesture affects the memorability of gestures (i.e., level of recall). In a user study, 35 participants used the HoloLens 2 to test three gestures set from different sources: 1) expert-defined, whereby we asked four experts to define gestures; 2) user-defined, whereby each participant defined their gestures; and 3) elicitation-defined, whereby we used gestures proposed by previous work. Our results showed that expert-defined gestures (72.73% recall) were more likely to be remembered than elicitation-defined (59.87% recall) gestures. Further, user-defined gestures (88.75% recall) were the most memorable. These data suggest that the source of gestures has a substantial impact on their memorability.

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.

Constant-and Dual-Threshold Dwell keyboards

In 3D environments, designing efficient notifications is crucial for capturing user attention. While visual notifications -such as objectattached and fixed-position ones- are commonly used in virtual environments, they often require users to shift their gaze away from task-relevant areas, which can interrupt workflow and delay responses. To address these limitations, we designed two gaze-based notification techniques to provide responsive and intuitive notification in a virtual reality (VR) cooking task. We evaluated four different notification types: two world-fixed notifications (onObject and onDock) and two gaze-based methods (GazeCue and Gaze+Dock) with 16 participants. Our results show that participants performed better in using gaze-based notifications compared to world-fixed ones. Questionnaire results indicated higher usability, greater perceived presence, and lower cognitive load for gaze-based notifications. These results highlight the effectiveness of gaze-based notification techniques in VR by reducing the need for visual search and minimizing cognitive load. Our findings provide insights for developers or engineers to design more intuitive and responsive user-interfaces for 3D environments.

Hand visualization significantly impacts user performance in virtual reality (VR), particularly in tasks requiring precise finger movements. Common hand avatar visualizations, such as opaque or transparent, often occlude critical elements or distract users, potentially reducing accuracy. To address this issue, we investigated adaptive hand visibility techniques, which vary the hand avatar visibility based on the current movement sub-task aiming to enhance user performance. We evaluated these techniques on a VR-based Pedicle Screw Placement task with 15 participants. Each participant inserted virtual screws into a spine using five hand visualization conditions: opaque, transparent, invisible, speed-based visibility (hand visibility changes with hand speed), and position-based visibility (hand visibility adapts to the proximity of critical elements). Results showed that speed-based and position-based visualizations significantly improved accuracy, usability, and overall performance compared to traditional methods. The widely adopted opaque visualization yielded the lowest accuracy and usability. Our findings emphasize the benefits of adaptive hand visualization based on sub-tasks, recommending its implementation in VR applications to increase usability and user accuracy.

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.

Any investigation of learning unfamiliar text entry systems is affected by the need to train participants on multiple new components simultaneously, such as novel interaction techniques and layouts. The Guided Evaluation Method (GEM) addresses this challenge by bypassing the need to learn layout-specific skills for text entry. However, a gap remains as the GEM's performance has not been assessed in situations where users are unfamiliar with the interaction technique involved, here eye-gaze-based dwell. To address this, we trained participants on only the eye-gaze-based interaction technique over eight days with QWERTY and then evaluated their performance on the OPTI layout with the GEM. Results showed that the unfamiliar OPTI layout outperformed QWERTY, with QWERTY's speed aligning with previous findings, suggesting that interaction technique expertise significantly impacts performance outcomes. Importantly, we also identified that for scenarios where the familiarity with the involved interaction technique(s) is the same, the GEM analyzes the performance of keyboard layouts effectively and quickly identifies the best option.

State-of-the-art Virtual Reality (VR) Head-Mounted Displays (HMDs) enable users to interact with virtual objects using their hands via built-in camera systems. However, the accuracy of the hand movement detection algorithm is often affected by limitations in both camera hardware and software, including image processing & machine learning algorithms used for hand skeleton detection. In this work, we investigated a visual feedback mechanism to create an early warning system that detects hand skeleton recognition failures in VR HMDs and warns users in advance. We conducted two user studies to evaluate the system's effectiveness. The first study involved a cup stacking task, where participants stacked virtual cups. In the second study, participants performed a ball sorting task, picking and placing colored balls into corresponding baskets. During both of the studies, we monitored the built-in hand tracking confidence of the VR HMD system and provided visual feedback to the user to warn them when the tracking confidence is 'low'. The results showed that warning users before the hand tracking algorithm fails improved the system's usability while reducing frustration. The impact of our results extends beyond VR HMDs, any system that uses hand tracking, such as robotics, can benefit from this approach.

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.

In Fitts’ law studies to investigate pointing, throughput is used to characterize the performance of input devices and users, which is claimed to be independent of task difficulty or the user’s subjective speed-accuracy bias. While throughput has been recognized as a useful metric for target-pointing tasks, the corresponding formulation for path-steering tasks and its evaluation have not been thoroughly examined in the past. In this paper, we conducted three experiments using linear, circular, and sine-wave path shapes to propose and investigate a novel formulation for the effective parameters and the throughput of steering tasks. Our results show that the effective width substantially improves the fit to data with mixed speed-accuracy biases for all task shapes. Effective width also smoothed out the throughput across all biases, while the usefulness of the effective amplitude depended on the task shape. Our study thus advances the understanding of user performance in trajectory-based tasks.

Virtual Reality (VR) applications like OpenBrush offer artists access to 3D sketching tools within the digital 3D virtual space. These 3D sketching tools allow users to “paint” using virtual digital strokes that emulate real-world mark-making. Yet, users paint these strokes through (unimodal) VR controllers. Given that sketching in VR is a relatively nascent field, this paper investigates ways to expand our understanding of sketching in virtual space, taking full advantage of what an immersive digital canvas offers. Through a study conducted with the participation of artists, we identify potential methods for natural multimodal and unimodal interaction techniques in 3D sketching. These methods demonstrate ways to incrementally improve existing interaction techniques and incorporate artistic feedback into the design.

Visual guides help to align strokes and raise accuracy in Virtual Reality (VR) sketching tools. Automatic guides that appear at relevant sketching areas are convenient to have for a seamless sketching with a guide. We explore guides that exploit eye-tracking to render them adaptive to the user’s visual attention. EyeGuide and EyeConGuide cause visual grid fragments to appear spatially close to the user’s intended sketches, based on the information of the user’s eye-gaze direction and the 3D position of the hand. Here we evaluated the techniques in two user studies across simple and complex sketching objectives in VR. The results show that gaze-based guides have a positive effect on sketching accuracy, perceived usability and preference over manual activation in the tested tasks. Our research contributes to integrating gaze-contingent techniques for assistive guides and presents important insights into multimodal design applications in VR.

In recent years, there has been a race among researchers, developers, engineers, and designers to come up with new interaction techniques for enhancing the performance and experience of users while interacting with virtual environments, and a key component of a 3D interaction technique is the selection technique. In this paper, we explore the environmental factors used in the assessment of 3D selection methods and classify each factor based on the task environment. Our approach consists of a thorough literature collection process, including four major Human-Computer Interaction repositories—Scopus, Science Direct, IEEE Xplore, and ACM Digital Library and created a dataset of a total of 277 papers. Drawing inspiration from the parameters outlined by LaViola et al. we manually classified each of those papers based on the task environment described in the papers. In addition, we explore the methodologies used in recent user studies to assess interaction techniques within various task environments, providing valuable insights into the developing landscape of virtual interaction research. We hope that the outcomes of our paper serve as a valuable resource for researchers, developers, and designers, providing a deeper understanding of task environments and offering fresh perspectives to evaluate their proposed 3D selection techniques in virtual environments.

In Virtual Reality (VR) applications, interacting with distant objects relies heavily on mid-air object manipulation. Yet, the inherent distance between the user and the object often restricts movement precision. This paper introduces the Signed Distance Field (SDF) method for mid-air object manipulation and combines it with the ray casting interaction technique to investigate its effect on user performance and user experience. To increase movement accuracy, we leverage the speed-accuracy trade-off to dynamically adjust object manipulation speed based on the SDF algorithm’s output. Our study with 18 participants examines the effects of SDF across three different tasks with different complexity. Our results showed that ray casting with SDF reduces the number of errors in complex tasks without slowing down the participants and improves the user experience. We hope that our proposed assistive system, designed for tasks and applications, can be used as an interaction technique to enable more accurate manipulation of distant objects in fields like surgical planning, architecture, and games.

Previous studies analyzed user motor performance with Virtual Reality (VR) and Augmented Reality (AR) Eye-Hand Coordination Training Systems (EHCTSs) while asking participants to follow specific task instructions. Although these studies suggested VR & AR EHCTSs as potential training systems for sports players, they recruited participants for their user studies among general population. In this paper, we examined the training performance of 16 professional volleyball players over 8 days using EHCTSs with three display technologies (VR, AR, and 2D touchscreen) and with four distinct task instructions (prioritizing speed, error rate, accuracy, or none). Our results indicate that volleyball players performed best with 2D touchscreen in terms of time, error rate, accuracy, precision, and throughput. Moreover, their performance was superior when using VR over AR. They also successfully followed the task instructions given to them and consistently improved their throughput performance. These findings underscore the potential of EHCTS in volleyball training and highlight the need for further research to optimize VR & AR user experience and performance.

Implementing visual and audio notifications on augmented reality devices is a crucial element of intuitive and easy-to-use interfaces. In this paper, we explored creating intuitive interfaces through visual and audio notifications. The study evaluated user performance and preference across three conditions: visual notifications in fixed positions, visual notifications above objects, and no visual notifications with monaural sounds. The users were tasked with cooking and serving customers in an open-source Augmented-Reality sandbox environment called ARtisan Bistro. The results indicated that visual notifications above objects combined with localized audio feedback were the most effective and preferred method by participants. The findings highlight the importance of strategic placement of visual and audio notifications in AR, providing insights for engineers and developers to design intuitive 3D user interfaces.

Modern Virtual Reality (VR) technology has enabled users to experience Real Environment (RE) sports in their homes. For VR table tennis, one of the most popular VR sports, the players have rankings and tournaments and compete for RE awards. Based on this phenomenon, this paper aims to understand the benefits of RE training in improving VR table tennis skills. In a user study with 12 novice table tennis players, we measured their performance in 16 basic skills via a pre- and post-study design using a novel training protocol designed for both RE and VR players. We also asked participants for their insights into the training and to evaluate their experience. Our results show a significant improvement in all measured skills. However, participants identified issues with the technology that caused discomfort. Our findings provide valuable insights for software developers working on VR sports applications, enabling them to create better experiences for VR table tennis players. They can also help developers of VR training applications identify areas for improvement with the current technology.

Previous studies on Eye-Hand Coordination Training (EHCT) focused on the comparison of user motor performance across different hardware with cross-sectional studies. In this paper, we compare user motor performance with an EHCT setup in Augmented Reality (AR), Virtual Reality (VR), and on a 2D touchscreen display in a longitudinal study. Through a ten-day user study, we thoroughly analyzed the motor performance of twenty participants with five task instructions focusing on speed, error rate, accuracy, precision, and none. As a novel evaluation criterion, we also analyzed the participants’ performance in terms of effective throughput. The results showed that each task instruction has a different effect on one or more psychomotor characteristics of the trainee, which highlights the importance of personalized training programs. Regarding different display technologies, the majority of participants could see more improvement in VR than in 2D or AR. We also identified that effective throughput is a good candidate for monitoring overall motor performance progress in EHCT systems.

During object manipulation in Virtual Reality (VR) systems, realistically visualizing avatars and objects can hinder user performance and experience by complicating the task or distracting the user from the environment due to possible occlusions. Users might feel the urge to go through biomechanical changes, such as re-positioning the head to visualize the interaction area. In this paper, we investigate the effect of hand avatar and object visibility in navigational tasks using a VR headset. We performed two user studies where participants grasped a small, cylindrical object and navigated it through the virtual obstacles performing rotational or translational movements. We used three different visibility conditions for the hand avatar (opaque, transparent, and invisible) and two conditions for the object (opaque and transparent). Our results indicate that participants performed faster and with fewer collisions using the invisible and transparent hands compared to the opaque hand and fewer collisions with the opaque object compared to the transparent one. Furthermore, participants preferred to use the combination of the transparent hand avatar with the opaque object. The findings of this study might be useful to researchers and developers in deciding the visibility/transparency conditions of hand avatars and virtual objects for tasks that require precise navigational activities.

While augmented reality (AR) headsets provide entirely new ways of seeing and interacting with data, traditional computing devices can play a symbiotic role when used in conjunction with AR as a hybrid user interface. A promising use case for this setup is situated analytics. AR can provide embedded views that are integrated with their physical referents, and a separate device such as a tablet can provide a familiar situated overview of the entire dataset being examined. While prior work has explored similar setups, we sought to understand how people perceive and make use of visualizations presented on both embedded visualizations (in AR) and situated visualizations (on a tablet) to achieve their own goals. To this end, we conducted an exploratory study using a scenario and task familiar to most: adjusting light levels in a smart home based on personal preference and energy usage. In a prototype that simulates AR in virtual reality, embedded visualizations are positioned next to lights distributed across an apartment, and situated visualizations are provided on a handheld tablet. We observed and interviewed 19 participants using the prototype. Participants were easily able to perform the task, though the extent the visualizations were used during the task varied, with some making decisions based on the data and others only on their own preferences. Our findings also suggest the two distinct roles that situated and embedded visualizations can have, and how this clear separation might improve user satisfaction and minimize attention-switching overheads in this hybrid user interface setup. We conclude by discussing the importance of considering the user's needs, goals, and the physical environment for designing and evaluating effective situated analytics applications.

Despite knowing exactly what an object looks like, searching for it in a person's visual field is a time-consuming and error-prone experience. In Augmented Reality systems, new algorithms are proposed to speed up search time and reduce human errors. However, these algorithms might not always provide 100% accurate visual cues, which might affect users' perceived reliability of the algorithm and, thus, search performance. Here, we examined the detrimental effects of automation bias caused by imperfect cues presented in the Augmented Reality head-mounted display using the YOLOv5 machine learning model. 53 participants in the two groups received either 100% accurate visual cues or 88.9% accurate visual cues. Their performance was compared with the control condition, which did not include any additional cues. The results show how cueing may increase performance and shorten search times. The results also showed that performance with imperfect automation was much worse than perfect automation and that, consistent with automation bias, participants were frequently enticed by incorrect cues.

When working in Virtual Reality (VR), the user’s performance is affected by how the user holds the input device (e.g., controller), typically using either a precision or a power grip. Previous work examined these grip styles for 3D pointing at targets at different depths in peripersonal space and found that participants had a lower error rate with the precision grip but identified no difference in movement speed, throughput, or interaction with target depth. Yet, this previous experiment was potentially affected by tracking differences between devices. This paper reports an experiment that partially replicates and extends the previous study by evaluating the effect of grip style on the 3D selection of nearby targets with the same device. Furthermore, our experiment re-investigates the effect of the vergence-accommodation conflict (VAC) present in current stereo displays on 3D pointing in peripersonal space. Our results show that grip style significantly affects user performance. We hope that our results are useful for researchers and designers when creating virtual environments.

The virtual hand interaction technique is one of the most common interaction techniques used in virtual reality (VR) systems. A VR application can be designed with different hand visualization styles, which might impact motor dexterity. In this paper, we aim to investigate the effects of three different hand visualization styles — transparent, opaque, and invisible — on participants’ performance through a VR-based Purdue Pegboard Test (PPT). A total of 24 participants were recruited and instructed to place pegs on the board as quickly and accurately as possible. The results indicated that using the invisible hand visualization significantly increased the number of task repetitions completed compared to the opaque hand visualization. However, no significant difference was observed in participants’ preference for the hand visualization styles. These findings suggest that an invisible hand visualization may enhance performance in the VR-based PPT, potentially indicating the advantages of a less obstructive hand visualization style. We hope our results can guide developers, researchers, and practitioners when designing novel virtual hand interaction techniques.

State-of-the-art Virtual Reality (VR) and Augmented Reality (AR) headsets rely on singlefocal stereo displays. For objects away from the focal plane, such displays create a vergence-accommodation conflict (VAC), potentially degrading user interaction performance. In this paper, we study how the VAC affects pointing at targets within arm's reach with virtual hand and raycasting interaction in current stereo display systems. We use a previously proposed experimental methodology that extends the ISO 9241–411:2015 multi-directional selection task to enable fair comparisons between selecting targets in different display conditions. We conducted a user study with eighteen participants and the results indicate that participants were faster and had higher throughput in the constant VAC condition with the virtual hand. We hope that our results enable designers to choose more efficient interaction methods in virtual environments.

The vergence-accommodation conflict (VAC) limits user performance in current Virtual Reality (VR) systems. In this paper, we investigate the effects of the VAC in a single-focal VR system using three experimental conditions: with no VAC, with a constant VAC, and with a varying VAC. Previous work in this area had yielded conflicting results, so we decided to re-investigate this issue. Eighteen participants performed an ISO 9241:411 task in a study that closely replicates previous work, except that the angle of the task space was rotated 20 degrees downward, to make the task less fatiguing to perform, which addresses a potential confound in previous work. We found that the varying VAC condition had worse performance than the other conditions, which indicates that the contrasting results in previous work were very likely due to biomechanical factors. We hope that our work contributes to the understanding of the influence of the VAC in VR systems and potential strategies for improving user experience and performance in immersive virtual environments.

Previous work hypothesized that for Virtual Reality (VR) and Augmented Reality (AR) displays a mismatch between disparities and optical focus cues, known as the vergence and accommodation conflict (VAC), affects depth perception and thus limits user performance in 3D selection tasks within arm’s reach (peri-personal space). To investigate this question, we built a multifocal stereo display, which can eliminate the influence of the VAC for pointing within the investigated distances. In a user study, participants performed a virtual hand 3D selection task with targets arranged laterally or along the line of sight, with and without a change in visual depth, in display conditions with and without the VAC. Our results show that the VAC influences 3D selection performance in common VR and AR stereo displays and that multifocal displays have a positive effect on 3D selection performance with a virtual hand.

Previous work has shown that the mismatch between disparity and optical focus cues, i.e., the vergence and accommodation conflict (VAC), affects virtual hand selection in immersive systems. To investigate if the VAC also affects distal pointing with ray casting, we ran a user study with an ISO 9241:411 multidirectional selection task where participants selected 3D targets with three different VAC conditions, no VAC, i.e., targets placed roughly at 75 cm, which matches the focal plane of the VR headset, constant VAC, i.e., at 400 cm from the user, and varying VAC, where the depth distance of targets changed between 75 cm and 400 cm. According to our results, the varying VAC condition requires the most time and decreases the throughput performance of the participants. It also takes longer for users to select targets in the constant VAC condition than without the VAC. Our results show that in distal pointing placing objects at different depth planes has detrimental effect on the user performance.

In eye-gaze-based selection, dwell suffers from several issues, e.g., the Midas Touch problem. Here we investigate saccade-based selection techniques as an alternative to dwell. First, we designed a novel user interface (UI) for Actigaze and used it with (goal-crossing) saccades for confirming the selection of small targets (i.e., < 1.5-2°). We compared it with three other variants of Actigaze (with button press, dwell, and target reverse crossing) and two variants of target magnification (with button press and dwell). Magnification-dwell exhibited the most promising performance. For Actigaze, goal-crossing was the fastest option but suffered the most errors. We then evaluated goal-crossing as a primary selection technique for normal-sized targets (≥ 2°) and implemented a novel UI for such interaction. Results revealed that dwell achieved the best performance. Yet, we identified goal-crossing as a good compromise between dwell and button press. Our findings thus identify novel options for gaze-only interaction.

Fitts' law and throughput based on effective measures are two mathematical models frequently used to analyze human motor performance in a standardized pointing task, e.g., to compare the performance of input and output devices. Even though pointing has been deeply studied in 2D, it is not well understood how different task execution strategies affect throughput in pointing in 3D virtual environments. In this work, we examine the effective throughput measure, claimed to be invariant to task execution strategies, in Virtual Reality (VR) systems with three such strategies, "as fast, as precise, and as fast and as precise as possible" for ray casting and virtual hand interaction, by re-analyzing data from a 3D pointing ISO 9241-411 study. Results show that effective throughput is not invariant for different task execution strategies in VR, which also matches a more recent 2D result. Normalized speed vs. accuracy curves also did not fit the data. We thus suggest that practitioners, developers, and researchers who use MacKenzie's effective throughput formulation should consider our findings when analyzing 3D user pointing performance in VR systems.

Fitts' law and the associated throughput measure characterize user pointing performance in virtual reality (VR) training systems and simulators well. Yet, pointing performance can be affected by the feedback users receive from a VR application. This work examines the effect of the pitch of auditory error feedback on user performance in a Fitts' task through a distributed experiment. In our first study, we used middle- and high-frequency sound feedback and demonstrated that high-pitch error feedback significantly decreases user performance in terms of time and throughput. In the second study, we used adaptive sound feedback, where we increased the frequency with the error rate, while asking subjects to execute the task “as fast/as precise/as fast and precise as possible”. Results showed that adaptive sound feedback decreases the error rate for “as fast as possible” task execution without affecting the time. The results can be used to enhance and design various VR systems.

Previous research on eye-hand coordination training systems has investigated user performance on a wall, 2D touchscreens, and in Virtual Reality (VR). In this paper, we designed an eye-hand coordination reaction test to investigate and compare user performance in three different virtual environments (VEs) – VR, Augmented Reality (AR), and a 2D touchscreen. VR and AR conditions also included two feedback conditions – mid-air and passive haptics. Results showed that compared to AR, participants were significantly faster and made fewer errors both in 2D and VR. However, compared to VR and AR, throughput performance of the participants was significantly higher in the 2D touchscreen condition. No significant differences were found between the two feedback conditions. The results show the importance of assessing precision and accuracy in eye-hand coordination training and suggest that it is currently not advisable to use AR headsets in such systems.

A relatively recent application area for Virtual Reality (VR) systems is sports training and user performance assessment. One of these applications is eye-hand coordination training systems (EHCTSs). Previous research identified that VR-based training systems have great potential for EHCTSs. While previous work investigated 3D targets on a 2D plane, here we aim to study full 3D movements and extend the application of throughput analysis to EHCTSs. We conducted two user studies to investigate how user performance is affected by different target arrangements, feedback conditions, and handedness in VR-based EHCTSs. In the first study, we explored handedness as well as vertical and horizontal target arrangements, and showed that user performance increases with the dominant hand and a vertical target plane. In the second study, we investigated different combinations of visual and haptic feedback and how they affect user performance with different target and cursor sizes. Results illustrate that haptic feedback did not increase user performance when it is added to visual feedback. Our results inform the creation of better EHCTSs with mid-air VR systems.

Most AR and VR headsets use stereoscopic displays to show virtual objects in 3D. However, the limitations of current stereo display systems affect depth perception through conflicting depth cues, which then also affect virtual hand interaction in peri-personal space, i.e., within arm's reach. We performed a Fitts' law experiment to better understand the impact of stereo display deficiencies of AR and VR headsets on pointing at close-by targets arranged laterally or along the line of sight. According to our results, the movement direction and the corresponding change in target depth affect pointing time and throughput; subjects' movements towards/away from their head were slower and less accurate than their lateral movements (left/right). However, even though subjects moved faster in AR, we did not observe a significant difference for pointing performance between AR and VR headsets, which means that previously identified differences in depth perception between these platforms seem to have no strong effect on interaction. Our results also help 3D user interface designers understand how changes in target depth affect users' performance in different movement directions in AR and VR.

3D pointing is an integral part of Virtual Reality interaction. Typical pointing devices rely on 3D trackers and are thus subject to fluctuations in the reported pose, i.e., jitter. In this work, we explored how different levels of rotational jitter affect pointing performance and if different selection methods can mitigate the effects of jitter. Towards this, we designed a Fitts' Law experiment with three selection methods. In the first method, subjects used a single controller to position and select the object. In the second method, subjects used the controller in their dominant hand to point at objects and the trigger button of a second controller, held in their non-dominant hand, to select objects. Finally, subjects used the controller in their dominant hand to point the objects and pressed the space bar on a keyboard to select the object in the third condition. During the pointing task we added five different levels of jitter: no jitter, ±0.5°, ±1°, and ±2° uniform noise, as well as White Gaussian noise with 1° standard deviation. Results showed that the Gaussian noise and ±2° of jitters significantly reduced the throughput of the participants. Moreover, subjects made fewer errors when they performed the experiment with two controllers. Our results inform the design of 3D user interfaces, input devices and interaction techniques.

Reaction time training systems are used to improve user performance. Until now, such setups use physical 2D flat surfaces, e.g., a 2D touch screen or buttons mounted on a wall. We designed and investigated a mid-air reaction time training system with an immersive virtual reality (VR) headset. 12 participants performed an eye-hand coordination reaction test in three conditions: both in mid-air with or without VR controller as well as with passive haptic feedback through hitting a soft-surface wall. We also altered target and cursor sizes and used a Fitts’ law task to analyze user performance. According to the results, subjects were slower and their throughput was lower when they hit a solid surface to interact with virtual targets. Our results show that Fitts’s model can be applied to these systems to measure and assess participant training.

The effective design of virtual reality (VR) simulators requires a deeper understanding of VR mediated human actions such as hand movements, with specifically tailored experiments testing how different design parameters affect performance. The present experiment investigates the time and precision of hand (index finger) movements under varying conditions of structural complexity and image size in VR without tactile feed-back from object to hand/finger. 18 right-handed subjects followed a complex and a simple physiological structure of small, medium and large size in VR, with the index finger of one of their two hands, from right to left, and from left to right. The results show that subjects performed best with small-size-simple structures and large-size-complex structures in VR. Movement execution was generally faster and more precise on simple structures. Performance was less precise when the dominant hand was used to follow the complex structures and small object size in VR. It is concluded that both size and structural complexity critically influence task execution in VR when no tactile feed-back from object to finger is generated. Individual learning curves should be monitored from the beginning of the training as suggested by the individual speed-precision analyses.

The occurrence of unidirectional links in wireless sensor networks (WSNs) is an inherent feature of wireless communication. Transceiver characteristics, asymmetric interference, and many other properties of the electromagnetic propagation environment result in link unidirectionality, however, transmission power heterogeneity is the dominant factor that creates unidirectional links. Most of the data transfer mechanisms designed for wireless networks work only on bidirectional links, yet, there are some mechanisms capable of utilizing unidirectional links. Employment of a multi-hop reverse path for acknowledgement delivery is the key concept and hop length of the reverse path is an important design criterion in such mechanisms. If the maximum reverse path length is allowed to take large values then the number of usable unidirectional links increases. Increasing the number of available links leads to better energy balancing and longer network lifetime. But is it necessary to keep the reverse path length large to achieve the maximum network lifetime possible? In this study, we investigate the effects of reverse path length in WSNs with unidirectional links induced by transmission power heterogeneity on network lifetime through a novel mixed integer programming framework. Our results show that reverse path length has significant impact on WSN lifetime.