Effects of Eye Vergence and Accommodation on Interactions with Content on an AR Magic-lens Display and its Surroundings.

Augmented reality (AR) magic-lens (ML) displays, such as handheld devices, offer a convenient and accessible way to enrich our environment using virtual imagery. Several display technologies, including conventional monocular, less common stereoscopic, and varifocal displays, are currently being used. Vergence and accommodation effects on depth perception, as well as vergence-accommodation conflict, have been studied, where users interact only with the content on the display. However, little research exists on how vergence and accommodation influence user performance and cognitive-task load when users interact with the content on a display and its surroundings in a short timeframe. Examples of this are validating augmented instructions before making an incision andperforming general hand-eye coordinated tasks such as grasping augmented objects. To improve interactions with future AR displays in such scenarios, we must improve our understanding of this influence. To this end, we conducted two fundamental visual-acuity user studies with 28 and 27 participants, while investigating eye vergence and accommodation distances on four ML displays. Our findings show that minimizing the accommodation difference between the display and its surroundings is crucial when the gaze between the display and its surroundings shifts rapidly. Minimizing the difference in vergence is more important when viewing the display and its surroundings as a single context without shifting the gaze. Interestingly, the vergence-accommodation conflict did not significantly affect the cognitive-task load nor play a pivotal role in the accuracy of interactions with AR ML content and its physical surroundings.

Development and Evaluation of Online Suicide Preventive Tool iAlive to Increase Competences in Engaging With a Suicidal Person.

Background: Online implementation of suicide prevention interventions offers many advantages, facilitating the dissemination of large-scale suicide prevention interventions. An online tool iAlive aimed at raising awareness and increasing suicide prevention competences in lay people was developed and implemented in Slovenia. Aims: To develop, implement, and evaluate the iAlive tool. Method: Following the development and implementation of the tool, a nonrandomized controlled study with 310 participants was conducted. One hundred fifty-six of them fully completed the study [intervention group (used the iAlive tool): N = 85, control group (did not use the tool): N = 71]. Perceived competences in engaging with a suicidal person were assessed in both groups at baseline and at follow-up (3-4 weeks apart), which also represents the time of the intervention. Results: A significant effect of time and condition [F(1,149) = 6.62, p = .011, ηp2 = .043] showed that the intervention group assessed their perceived competences on intervention exposure more positively compared to the control group. Limitations: Additional data on different populations and people's engagement with the tool in relation to perceived competences are needed. Conclusion: The study suggests that the interactive online tool iAlive effectively increases perceived competences in engaging with a suicidal person. These results provide a background for further dissemination of the tool.

Arigato: Effects of Adaptive Guidance On Engagement and Performance in Augmented Reality Learning Environments.

Experiential learning (ExL) is the process of learning through experience or more specifically "learning through reflection on doing". In this paper, we propose a simulation of these experiences, in Augmented Reality (AR), addressing the problem of language learning. Such systems provide an excellent setting to support "adaptive guidance", in a digital form, within a real environment. Adaptive guidance allows the instructions and learning content to be customised for the individual learner, thus creating a unique learning experience. We developed an adaptive guidance AR system for language learning, we call Arigato (Augmented Reality Instructional ¯ Guidance & Tailored Omniverse), which offers immediate assistance, resources specific to the learner's needs, manipulation of these resources, and relevant feedback. Considering guidance, we employ this prototype to investigate the effect of the amount of guidance (fixed vs. adaptive-amount) and the type of guidance (fixed vs. adaptive-associations) on the engagement and consequently the learning outcomes of language learning in an AR environment. The results for the amount of guidance show that compared to the adaptive-amount, the fixed-amount of guidance group scored better in the immediate and delayed (after 7 days) recall tests. However, this group also invested a significantly higher mental effort to complete the task. The results for the type of guidance show that the adaptive-associations group outperforms the fixed-associations group in the immediate, delayed (after 7 days) recall tests, and learning efficiency. The adaptive-associations group also showed significantly lower mental effort and spent less time to complete the task.

The Hybrid Stylus: A Multi-Surface Active Stylus for Interacting with and Handwriting on Paper, Tabletop Display or Both.

The distinct properties and affordances of paper provide benefits that enabled paper to maintain an important role in the digital age. This is so much so, that some pen-paper interaction has been imitated in the digital world with touchscreens and stylus pens. Because digital medium also provides several advantages not available to physical paper, there is a clear benefit to merge the two mediums. Despite the plethora of concepts, prototypes and systems to digitise handwritten information on paper, these systems require specially prepared paper, complex setups and software, which can be used solely in combination with paper, and, most importantly, do not support the concurrent precise interaction with both mediums (paper and touchscreen) using one pen only. In this paper, we present the design, fabrication and evaluation of the Hybrid Stylus. The Hybrid Stylus is assembled with the infinity pencil tip (nib) made of graphite and a specially designed shielded tip holder that is attached to an active stylus. The stylus can be used for writing on a physical paper, while it still maintains all the features needed for tablet interaction. Moreover, the stylus also allows simultaneous digitisation of handwritten information on the paper when the paper is placed on the tablet screen. In order to evaluate the concept, we also add a user-friendly manual alignment of paper position on the underlying tablet computer The evaluation demonstrates that the system achieves almost perfect digitisation of strokes (98.6% of strokes were correctly registered with only 1.2% of ghost strokes) whilst maintaining excellent user experience of writing with a pencil on the paper.

VocabulARy: Learning Vocabulary in AR Supported by Keyword Visualisations.

Learning vocabulary in a primary or secondary language is enhanced when we encounter words in context. This context can be afforded by the place or activity we are engaged with. Existing learning environments include formal learning, mnemonics, flashcards, use of a dictionary or thesaurus, all leading to practice with new words in context. In this work, we propose an enhancement to the language learning process by providing the user with words and learning tools in context, with VocabulARy. VocabulARy visually annotates objects in AR, in the user's surroundings, with the corresponding English (first language) and Japanese (second language) words to enhance the language learning process. In addition to the written and audio description of each word, we also present the user with a keyword and its visualisation to enhance memory retention. We evaluate our prototype by comparing it to an alternate AR system that does not show an additional visualisation of the keyword, and, also, we compare it to two non-AR systems on a tablet, one with and one without visualising the keyword. Our results indicate that AR outperforms the tablet system regarding immediate recall, mental effort and task-completion time. Additionally, the visualisation approach scored significantly higher than showing only the written keyword with respect to immediate and delayed recall and learning efficiency, mental effort and task-completion time.

Quantifying the Effects of Working in VR for One Week.

Virtual Reality (VR) provides new possibilities for modern knowledge work. However, the potential advantages of virtual work environments can only be used if it is feasible to work in them for an extended period of time. Until now, there are limited studies of long-term effects when working in VR. This paper addresses the need for understanding such long-term effects. Specifically, we report on a comparative study $i$, in which participants were working in VR for an entire week-for five days, eight hours each day-as well as in a baseline physical desktop environment. This study aims to quantify the effects of exchanging a desktop-based work environment with a VR-based environment. Hence, during this study, we do not present the participants with the best possible VR system but rather a setup delivering a comparable experience to working in the physical desktop environment. The study reveals that, as expected, VR results in significantly worse ratings across most measures. Among other results, we found concerning levels of simulator sickness, below average usability ratings and two participants dropped out on the first day using VR, due to migraine, nausea and anxiety. Nevertheless, there is some indication that participants gradually overcame negative first impressions and initial discomfort. Overall, this study helps lay the groundwork for subsequent research, by clearly highlighting current shortcomings and identifying opportunities for improving the experience of working in VR.

PoVRPoint: Authoring Presentations in Mobile Virtual Reality.

Virtual Reality (VR) has the potential to support mobile knowledge workers by complementing traditional input devices with a large three-dimensional output space and spatial input. Previous research on supporting VR knowledge work explored domains such as text entry using physical keyboards and spreadsheet interaction using combined pen and touch input. Inspired by such work, this paper probes the VR design space for authoring presentations in mobile settings. We propose PoVRPoint-a set of tools coupling pen- and touch-based editing of presentations on mobile devices, such as tablets, with the interaction capabilities afforded by VR. We study the utility of extended display space to, for example, assist users in identifying target slides, supporting spatial manipulation of objects on a slide, creating animations, and facilitating arrangements of multiple, possibly occluded shapes or objects. Among other things, our results indicate that 1) the wide field of view afforded by VR results in significantly faster target slide identification times compared to a tablet-only interface for visually salient targets; and 2) the three-dimensional view in VR enables significantly faster object reordering in the presence of occlusion compared to two baseline interfaces. A user study further confirmed that the interaction techniques were found to be usable and enjoyable.

No Interface, No Problem: Gesture Recognition on Physical Objects Using Radar Sensing.

Physical objects are usually not designed with interaction capabilities to control digital content. Nevertheless, they provide an untapped source for interactions since every object could be used to control our digital lives. We call this the missing interface problem: Instead of embedding computational capacity into objects, we can simply detect users' gestures on them. However, gesture detection on such unmodified objects has to date been limited in the spatial resolution and detection fidelity. To address this gap, we conducted research on micro-gesture detection on physical objects based on Google Soli's radar sensor. We introduced two novel deep learning architectures to process range Doppler images, namely a three-dimensional convolutional neural network (Conv3D) and a spectrogram-based ConvNet. The results show that our architectures enable robust on-object gesture detection, achieving an accuracy of approximately 94% for a five-gesture set, surpassing previous state-of-the-art performance results by up to 39%. We also showed that the decibel (dB) Doppler range setting has a significant effect on system performance, as accuracy can vary up to 20% across the dB range. As a result, we provide guidelines on how to best calibrate the radar sensor.