TY - JOUR A1 - Halbig , Andreas A1 - Babu , Sooraj K. A1 - Gatter , Shirin A1 - Latoschik , Marc Erich A1 - Brukamp, Kirsten A1 - von Mammen , Sebastian T1 - Opportunities and challenges of Virtual Reality in healthcare – a domain experts inquiry JF - Frontiers in Virtual Reality N2 - In recent years, the applications and accessibility of Virtual Reality (VR) for the healthcare sector have continued to grow. However, so far, most VR applications are only relevant in research settings. Information about what healthcare professionals would need to independently integrate VR applications into their daily working routines is missing. The actual needs and concerns of the people who work in the healthcare sector are often disregarded in the development of VR applications, even though they are the ones who are supposed to use them in practice. By means of this study, we systematically involve health professionals in the development process of VR applications. In particular, we conducted an online survey with 102 healthcare professionals based on a video prototype which demonstrates a software platform that allows them to create and utilise VR experiences on their own. For this study, we adapted and extended the Technology Acceptance Model (TAM). The survey focused on the perceived usefulness and the ease of use of such a platform, as well as the attitude and ethical concerns the users might have. The results show a generally positive attitude toward such a software platform. The users can imagine various use cases in different health domains. However, the perceived usefulness is tied to the actual ease of use of the platform and sufficient support for learning and working with the platform. In the discussion, we explain how these results can be generalized to facilitate the integration of VR in healthcare practice. KW - virtual reality KW - healthcare KW - therapy KW - rehabilitation KW - ethics KW - technology acceptance KW - authoring platform KW - healthcare professionals Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-284752 SN - 2673-4192 VL - 3 ER - TY - JOUR A1 - Donnermann, Melissa A1 - Schaper, Philipp A1 - Lugrin, Birgit T1 - Social robots in applied settings: a long-term study on adaptive robotic tutors in higher education JF - Frontiers in Robotics and AI N2 - Learning in higher education scenarios requires self-directed learning and the challenging task of self-motivation while individual support is rare. The integration of social robots to support learners has already shown promise to benefit the learning process in this area. In this paper, we focus on the applicability of an adaptive robotic tutor in a university setting. To this end, we conducted a long-term field study implementing an adaptive robotic tutor to support students with exam preparation over three sessions during one semester. In a mixed design, we compared the effect of an adaptive tutor to a control condition across all learning sessions. With the aim to benefit not only motivation but also academic success and the learning experience in general, we draw from research in adaptive tutoring, social robots in education, as well as our own prior work in this field. Our results show that opting in for the robotic tutoring is beneficial for students. We found significant subjective knowledge gain and increases in intrinsic motivation regarding the content of the course in general. Finally, participation resulted in a significantly better exam grade compared to students not participating. However, the extended adaptivity of the robotic tutor in the experimental condition did not seem to enhance learning, as we found no significant differences compared to a non-adaptive version of the robot. KW - human-robot interaction KW - adaptive tutoring KW - higher education KW - robot-supported training KW - technology-supported education KW - robotic tutor Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-266012 SN - 2296-9144 VL - 9 ER - TY - JOUR A1 - Hartelt, Alexander A1 - Puppe, Frank T1 - Optical Medieval Music Recognition using background knowledge JF - Algorithms N2 - This paper deals with the effect of exploiting background knowledge for improving an OMR (Optical Music Recognition) deep learning pipeline for transcribing medieval, monophonic, handwritten music from the 12th–14th century, whose usage has been neglected in the literature. Various types of background knowledge about overlapping notes and text, clefs, graphical connections (neumes) and their implications on the position in staff of the notes were used and evaluated. Moreover, the effect of different encoder/decoder architectures and of different datasets for training a mixed model and for document-specific fine-tuning based on an extended OMR pipeline with an additional post-processing step were evaluated. The use of background models improves all metrics and in particular the melody accuracy rate (mAR), which is based on the insert, delete and replace operations necessary to convert the generated melody into the correct melody. When using a mixed model and evaluating on a different dataset, our best model achieves without fine-tuning and without post-processing a mAR of 90.4%, which is raised by nearly 30% to 93.2% mAR using background knowledge. With additional fine-tuning, the contribution of post-processing is even greater: the basic mAR of 90.5% is raised by more than 50% to 95.8% mAR. KW - Optical Music Recognition KW - historical document analysis KW - medieval manuscripts KW - neume notation KW - fully convolutional neural networks KW - background knowledge Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-278756 SN - 1999-4893 VL - 15 IS - 7 ER - TY - JOUR A1 - Döllinger, Nina A1 - Wolf, Erik A1 - Mal, David A1 - Wenninger, Stephan A1 - Botsch, Mario A1 - Latoschik, Marc Erich A1 - Wienrich, Carolin T1 - Resize Me! Exploring the user experience of embodied realistic modulatable avatars for body image intervention in virtual reality JF - Frontiers in Virtual Reality N2 - Obesity is a serious disease that can affect both physical and psychological well-being. Due to weight stigmatization, many affected individuals suffer from body image disturbances whereby they perceive their body in a distorted way, evaluate it negatively, or neglect it. Beyond established interventions such as mirror exposure, recent advancements aim to complement body image treatments by the embodiment of visually altered virtual bodies in virtual reality (VR). We present a high-fidelity prototype of an advanced VR system that allows users to embody a rapidly generated personalized, photorealistic avatar and to realistically modulate its body weight in real-time within a carefully designed virtual environment. In a formative multi-method approach, a total of 12 participants rated the general user experience (UX) of our system during body scan and VR experience using semi-structured qualitative interviews and multiple quantitative UX measures. Using body weight modification tasks, we further compared three different interaction methods for real-time body weight modification and measured our system’s impact on the body image relevant measures body awareness and body weight perception. From the feedback received, demonstrating an already solid UX of our overall system and providing constructive input for further improvement, we derived a set of design guidelines to guide future development and evaluation processes of systems supporting body image interventions. KW - virtual reality KW - avatar embodiment KW - user experience KW - body awareness KW - body weight perception KW - body weight modification KW - body image disturbance KW - eating and body weight disorders Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-292940 SN - 2673-4192 VL - 3 ER -