Test2

Nurses frequently transfer patients as part of their daily work. However, manual patient transfers pose a major risk to nurses’ health. Although the Kinaesthetics care conception can help address this issue, existing support to learn the concept is low. We present KiTT, a tablet-based system, to promote the learning of ergonomic patient transfers based on the Kinaesthetics care conception. KiTT supports the training of Kinaesthetics-based patient transfers by two nurses. The nurses are guided by the phases (i) interactive instructions, (ii) training of transfer conduct, and (iii) feedback and reflection. We evaluated KiTT with 26 nursing-care students in a nursing-care school. Our results indicate that KiTT provides a good subjective support for the learning of Kinaesthetics. Our results also suggest that KiTT can promote the ergonomically correct conduct of patient transfers while providing a good user experience adequate to the nursing-school context, and reveal how KiTT can extend existing practices.

Arm discomfort is a common issue in Cross Reality applications involving prolonged mid-air interaction. Solving this problem is difficult because of the lack of tools and guidelines for 3D user interface design. Therefore, we propose a method to make existing ergonomic metrics available to creators during design by estimating the interaction cost at each reachable position in the user’s environment. We present XRgonomics, a toolkit to visualize the interaction cost and make it available at runtime, allowing creators to identify UI positions that optimize users’ comfort. Two scenarios show how the toolkit can support 3D UI design and dynamic adaptation of UIs based on spatial constraints. We present results from a walkthrough demonstration, which highlight the potential of XRgonomics to make ergonomics metrics accessible during the design and development of 3D UIs. Finally, we discuss how the toolkit may address design goals beyond ergonomics.

Recent research in the area of immersive analytics demonstrated the utility of head-mounted augmented reality devices for visual data analysis. However, it can be challenging to use the by default supported mid-air gestures to interact with visualizations in augmented reality (e.g. due to limited precision). Touch-based interaction (e.g. via mobile devices) can compensate for these drawbacks, but is limited to two-dimensional input. In this work we present STREAM: Spatially-aware Tablets combined with Augmented Reality Head-Mounted Displays for the multimodal interaction with 3D visualizations. We developed a novel eyes-free interaction concept for the seamless transition between the tablet and the augmented reality environment. A user study reveals that participants appreciated the novel interaction concept, indicating the potential for spatially-aware tablets in augmented reality. Based on our findings, we provide design insights to foster the application of spatially-aware touch devices in augmented reality and research implications indicating areas that need further investigation.

Research paper recommender systems are widely used by academics to discover and explore the most relevant publications on a topic. While existing recommendation interfaces present researchers with a ranked list of publications based on a global relevance score, they fail to visualize the full range of non-textual features uniquely present in academic publications: citations, figures, charts, or images, and mathematical formulae or expressions. Especially for STEM literature, examining such non-textual features efficiently can provide utility to researchers interested in answering specialized research questions or information needs. If research paper search and recommender systems are to consider the similarity of such features as one facet of a content-based similarity assessment for academic literature, new methods for visualizing these non-textual features are needed. In this paper, we review the state-of-the-art in visualizing feature-based similarity in documents. We subsequently propose a set of user-customizable visualization approaches tailored to STEM literature and the research paper recommendation context. Results from a study with 10 expert users show that the interactive visualization interface we propose for the exploration of non-textual features in publications can effectively address specialized information retrieval tasks, which cannot be addressed by existing research paper search or recommendation interfaces.

Transitional interfaces (TIs) and related concepts such as cross-reality (XR) or cross-virtuality (XV) are key topics for future HCI and AR/VR research. Future TIs will enable users to freely move between different locations within the reality-virtuality continuum during work, to choose the best technologies for their task at hand and current information need. Our workshop will explore the core advantages and challenges of TIs and related concepts and address them in presentations and workshop activities at ACM ISS 2021.

Airlines and flying schools use high-end physical flight simulators (PFS) to reduce costs and risks of pilot training. However, such PFS with full-scale cockpits have very high acquisition and operation costs. In contrast, recent consumer-grade and off-the-shelf soft- and hardware can be used to create increasingly realistic virtual reality flight simulators (VRFS) that could potentially serve as cost-efficient and flexible alternatives. We present a user study with 11 participants to determine whether consumer-grade VRFS can supplement or even replace a PFS during cockpit familiarization training (CFT). We compared a full-scale Boeing 737-800NG PFS with a VRFS based on off-the-shelf flight simulator software combined with a consumer-grade head-mounted display and either finger tracking or a handheld controller as input device. Participants performed instrument reading tasks and check procedures from the aircraft’s operating manual. We did not observe statistically significant differences in successful instrument reading tasks, error rates and task completion between PFS and VRFS during CFT. However, we found that VRFS’ Mental Demand, Physical Demand, Effort, task completion times, and levels of simulator sickness were significantly higher and exceeded acceptable levels. We conclude that future consumer-grade VRFS will need to improve soft- and hard- ware for interacting with simulated switches and reduce simulator sickness before they can serve as PFS alternatives for CFT.

dc.title:

dc.contributor.author: Belo, João; Hwang, Chiwoong; Lunding, Rasmus; Lystbæk, Mathias; Pfeuffer, Ken; Rasmussen, Troels

While patient transfers are part of nurses’ daily work, the manual transfer of patients can also pose a major risk to nurses’ health. The Kinaesthetics care conception may help nurses to conduct patient transfers more ergonomically. However, existing support to learn the concept is low. We introduce ViTT, a Virtual Reality system to promote the individual, self-directed learning of ergonomic patient transfers based on the Kinaesthetics care conception. The current implementation of ViTT supports a nurse in two phases: (i) instructions for a patient transfer, and (ii) training of the transfer with a virtual patient (based on a physics engine; implementation limited). In contrast to previous work, our approach provides an immersive experience that may allow for the ‘safe’ training of different transfer scenarios—e.g., patients with different impairments—and the study of different parameters that may influence nurses’ learning experience—e.g., the simulation of stress—in the future.

dc.title:

Augmented Reality (AR) supported collaboration is a popular topic in HCI research. Previous work has shown the benefits of collaborative 3D object manipulation and identified two possibilities: Either separate or compose users’ inputs. However, their experimental comparison using handheld AR displays is still missing. We, therefore, conducted an experiment in which we tasked 24 dyads with collaboratively positioning virtual objects in handheld AR using three manipulation techniques: 1) Separation – performing only different manipulation tasks (i. e., translation or rotation) simultaneously, 2) Composition – performing only the same manipulation tasks simultaneously and combining individual inputs using a merge policy, and 3) Hybrid – performing any manipulation tasks simultaneously, enabling dynamic transitions between Separation and Composition. While all techniques were similarly effective, Composition was least efficient, with higher subjective workload and worse user experience. Preferences were polarized between clear work division (Separation) and freedom of action (Hybrid). Based on our findings, we offer research and design implications.

Mobile intervention studies employ mobile devices to observe participants’ behavior change over several weeks. Researchers regularly monitor high-dimensional data streams to ensure data quality and prevent data loss (e.g., missing engagement or malfunctions). The multitude of problem sources hampers possible automated detection of such irregularities – providing a use case for interactive dashboards. With the advent of untethered head-mounted AR devices, these dashboards can be placed anywhere in the user's physical environment, leveraging the available space and allowing for flexible information arrangement and natural navigation. In this work, we present the user-centered design and the evaluation of IDIAR: Interactive Dashboards in AR, combining a head-mounted display with the familiar interaction of a smartphone. A user study with 15 domain experts for mobile intervention studies shows that participants appreciated the multimodal interaction approach. Based on our findings, we provide implications for research and design of interactive dashboards in AR.

dc.title:

dc.contributor.author: Mayer, Janine; Friedl, Judith; Anthes, Christoph

Through technological advancements more and more companies consider virtual reality (VR) for training of their workforce, in particular for situations that occur rarely, are dangerous, expensive, or very difficult to recreate in the real world. This creates the need for understanding the potentials and limitations of VR training and establish best practices. In pursuit of this, we have developed a VR Training simulation for a use case at Grundfos, in which apprentices learn a sequential maintenance task. We evaluated this simulation in a user study with 36 participants, comparing it to two traditional forms of training (Pairwise Training and Video Training). This case study describes the developed virtual training scenario and discusses design considerations for such VR simulations. The results of our evaluation support that, while VR Training is effective in teaching the procedure for a maintenance task, traditional approaches with hands-on experience still lead to a significantly better outcome.

The interaction with distant displays often demands complex, multi-modal inputs which need to be achieved with a very simple hardware solution so that users can perform rich inputs wherever they encounter a distant display. We present Simo, a novel approach, that transforms a regular smartphone into a highly-expressive user motion tracking device and controller for distant displays. Both the front and back cameras of the smartphone are used simultaneously to track the user’s hand as well as the head, and body movements in real-world space and scale. In this work, we first define the possibilities for simultaneous face- and world-tracking using current off-the-shelf smartphones. Next, we present the implementation of a smartphone app enabling hand, head, and body motion tracking. Finally, we present a technical analysis outlining the possible tracking range.

Programming assignments in computer science courses are often processed in pairs or groups of students. While working together, students face several shortcomings in today's software: The lack of real-time collaboration capabilities, the setup time of the development environment, and the use of different devices or operating systems can hamper students when working together on assignments. Text processing platforms like Google Docs solve these problems for the writing process of prose text, and computational notebooks like Google Colaboratory for data analysis tasks. However, none of these platforms allows users to implement interactive applications. We deployed a web-based literate programming system for three months during an introductory course on application development to explore how collaborative programming practices unfold and how the structure of computational notebooks affect the development. During the course, pairs of students solved weekly programming assignments. We analyzed data from weekly questionnaires, three focus groups with students and teaching assistants, and keystroke-level log data to facilitate the understanding of the subtleties of collaborative programming with computational notebooks. Findings reveal that there are distinct collaboration patterns; the preferred collaboration pattern varied between pairs and even varied within pairs over the course of three months. Recognizing these distinct collaboration patterns can help to design future computational notebooks for collaborative programming assignments.

Cross-device interaction with tablets is a popular topic in HCI research. Recent work has shown the benefits of including multiple devices into users’ workflows while various interaction techniques allow transferring content across devices. However, users are only reluctantly using multiple devices in combination. At the same time, research on cross-device interaction struggles to find a frame of reference to compare techniques or systems. In this paper, we try to address these challenges by studying the interplay of interaction techniques, device utilization, and task-specific activities in a user study with 24 participants from different but complementary angles of evaluation using an abstract task, a sensemaking task, and three interaction techniques. We found that different interaction techniques have a lower influence than expected, that work behaviors and device utilization depend on the task at hand, and that participants value specific aspects of cross-device interaction.

dc.title:

Nurses are frequently required to transfer patients as part of their daily duties. However, the manual transfer of patients is a major risk factor for injuries to the back. Although the Kinaesthetics Care Conception can help to address this issue, existing support for the integration of the concept into nursing-care practice is low. We present NurseCare, a mobile system that aims to promote the practical application of ergonomic patient transfers based on the Kinaesthetics Care Conception. NurseCare consists of a wearable and a smartphone app. Key features of NurseCare include mobile accessible instructions for ergonomic patient transfers, in-situ feedback for the risky bending of the back, and long-term feedback. We evaluated NurseCare in a nine participant 'in-the-wild' evaluation. Results indicate that NurseCare can facilitate ergonomic work while providing a high user experience adequate to the nurses' work domain, and reveal how NurseCare can be incorporated in given practices.

Collaboration in virtual reality (VR) across heterogeneous devices poses challenges for effectively supporting manipulation, navigation, and communication through different interfaces. We explored these in the design and development of a collaborative VR system that allows interaction through a mobile touchscreen device (Handheld User) and a head-mounted display (HMD User). In a qualitative evaluation, we further analyzed how these interfaces affect social roles and user interactions during collaboration. Our observations reveal that Handheld Users achieved presence in the virtual environment, despite the non-immersive interface, and assumed similar spatial positions in a conversational scenario as they would in the real world. In a collaborative building task, we found leadership roles not tied to immersion, but potentially influenced by users’ eye-level. Further, Handheld Users exhibited stronger movement patterns than HMD Users. Based on such behavioral patterns, we contribute a classification framework for Handheld Users that facilitates future analysis of interactions in shared virtual environments through handheld devices. Finally, we offer several design considerations for collaborative cross-device VR, which are based on our observations and exemplified in our presented system.