“Real Change Comes from Within!”: Towards a Symbiosis of Human and Digital Guides in the Museum

Extensive research on mobile guides for museums has explored the potential of technology to offer some of the services that have been traditionally provided by human guides, including guiding visitors in the museum space, providing information about the exhibits, and using more advanced interpretative approaches such as digital storytelling and gamified techniques. However, the majority of these approaches either ignores or tries to substitute entirely the role of the human guide. In this work, we present a user study with 10 experienced tour guides, currently working in the museum of modern art of the Basil & Elise Goulandris Foundation. Based on a three-phase procedure, the study is designed to empower professionals into envisaging their work in symbiosis with current technological developments. First, we attempt to identify existing challenges guides face and to capture their tacit knowledge in addressing emerging problems in guided tours. In the second and third stage, through a reflective and productive discussion, we employ a set of contemporary innovative digital applications as a starting point to elicit their views on their role in an envisaged symbiotic future of human-led hybrid digital experiences.

Towards Tangible Cultural Heritage Experiences—Enriching VR-based Object Inspection with Haptic Feedback

VR/AR technology is a key enabler for new ways of immersively experiencing cultural heritage artifacts based on their virtual counterparts obtained from a digitization process. In this article, we focus on enriching VR-based object inspection by additional haptic feedback, thereby creating tangible cultural heritage experiences. For this purpose, we present an approach for interactive and collaborative VR-based object inspection and annotation. Our system supports high-quality 3D models with accurate reflectance characteristics while additionally providing haptic feedback regarding shape features of the object based on a 3D printed replica. The digital object model in terms of a printable representation of the geometry as well as reflectance characteristics are stored in a compact and streamable representation on a central server, which streams the data to remotely connected users/clients. The latter can jointly perform an interactive inspection of the object in VR with additional haptic feedback through the 3D printed replica. Evaluations regarding system performance, visual quality of the considered models, as well as insights from a user study indicate an improved interaction, assessment, and experience of the considered objects.

Coordinating Human-Robot Teams with Dynamic and Stochastic Task Proficiencies

As robots become ubiquitous in the workforce, it is essential that human-robot collaboration be both intuitive and adaptive. A robot’s ability to coordinate team activities improves based on its ability to infer and reason about the dynamic (i.e., the “learning curve”) and stochastic task performance of its human counterparts. We introduce a novel resource coordination algorithm that enables robots to schedule team activities by (1) actively characterizing the task performance of their human teammates and (2) ensuring the schedule is robust to temporal constraints given this characterization. We first validate our modeling assumptions via user study. From this user study, we create a data-driven prior distribution over human task performance for our virtual and physical evaluations of human-robot teaming. Second, we show that our methods are scalable and produce high-quality schedules. Third, we conduct a between-subjects experiment (n = 90) to assess the effects on a human-robot team of a robot scheduler actively exploring the humans’ task proficiency. Our results indicate that human-robot working alliance ( p\lt 0.001 ) and human performance ( p=0.00359 ) are maximized when the robot dedicates more time to exploring the capabilities of human teammates.

Guided Feature Identification and Removal for Resource-constrained Firmware

IoT firmware oftentimes incorporates third-party components, such as network-oriented middleware and media encoders/decoders. These components consist of large and mature codebases, shipping with a variety of non-critical features. Feature bloat increases code size, complicates auditing/debugging, and reduces stability. This is problematic for IoT devices, which are severely resource-constrained and must remain operational in the field for years. Unfortunately, identification and complete removal of code related to unwanted features requires familiarity with codebases of interest, cumbersome manual effort, and may introduce bugs. We address these difficulties by introducing PRAT, a system that takes as input the codebase of software of interest, identifies and maps features to code, presents this information to a human analyst, and removes all code belonging to unwanted features. PRAT solves the challenge of identifying feature-related code through a novel form of differential dynamic analysis and visualizes results as user-friendly feature graphs . Evaluation on diverse codebases shows superior code removal compared to both manual feature deactivation and state-of-art debloating tools, and generality across programming languages. Furthermore, a user study comparing PRAT to manual code analysis shows that it can significantly simplify the feature identification workflow.

Creating and Augmenting Keyboards for Extended Reality with the K eyboard A ugmentation T oolkit

This article discusses the Keyboard Augmentation Toolkit (KAT), which supports the creation of virtual keyboards that can be used both for standalone input (e.g., for mid-air text entry) and to augment physically tracked keyboards/surfaces in mixed reality. In a user study, we firstly examine the impact and pitfalls of visualising shortcuts on a tracked physical keyboard, exploring the utility of virtual per-keycap displays. Supported by this and other recent developments in XR keyboard research, we then describe the design, development, and evaluation-by-demonstration of KAT. KAT simplifies the creation of virtual keyboards (optionally bound to a tracked physical keyboard) that support enhanced display —2D/3D per-key content that conforms to the virtual key bounds; enhanced interactivity —supporting extensible per-key states such as tap, dwell, touch, swipe; flexible keyboard mappings that can encapsulate groups of interaction and display elements, e.g., enabling application-dependent interactions; and flexible layouts —allowing the virtual keyboard to merge with and augment a physical keyboard, or switch to an alternate layout (e.g., mid-air) based on need. Through these features, KAT will assist researchers in the prototyping, creation and replication of XR keyboard experiences, fundamentally altering the keyboard’s form and function.

An Exploratory Study on the Acoustic Musical Properties to Decrease Self-Perceived Anxiety

Musical listening is broadly used as an inexpensive and safe method to reduce self-perceived anxiety. This strategy is based on the emotivist assumption claiming that emotions are not only recognised in music but induced by it. Yet, the acoustic properties of musical work capable of reducing anxiety are still under-researched. To fill this gap, we explore whether the acoustic parameters relevant in music emotion recognition are also suitable to identify music with relaxing properties. As an anxiety indicator, the positive statements from the six-item Spielberger State-Trait Anxiety Inventory, a self-reported score from 3 to 12, are taken. A user-study with 50 participants assessing the relaxing potential of four musical pieces was conducted; subsequently, the acoustic parameters were evaluated. Our study shows that when using classical Western music to reduce self-perceived anxiety, tonal music should be considered. In addition, it also indicates that harmonicity is a suitable indicator of relaxing music, while the role of scoring and dynamics in reducing non-pathological listener distress should be further investigated.

Adaptive Playback Control: A Framework for Cinematic VR Creators to Embrace Viewer Interaction

Content creators have been trying to produce engaging and enjoyable Cinematic Virtual Reality (CVR) experiences using immersive media such as 360-degree videos. However, a complete and flexible framework, like the filmmaking grammar toolbox for film directors, is missing for creators working on CVR, especially those working on CVR storytelling with viewer interactions. Researchers and creators widely acknowledge that a viewer-centered story design and a viewer’s intention to interact are two intrinsic characteristics of CVR storytelling. In this paper, we stand on that common ground and propose Adaptive Playback Control (APC) as a set of guidelines to assist content creators in making design decisions about the story structure and viewer interaction implementation during production. Instead of looking at everything CVR covers, we set constraints to focus only at cultural heritage oriented content using a guided-tour style. We further choose two vital elements for interactive CVR: the narrative progression (director vs. viewer control) and visibility of viewer interaction (implicit vs. explicit) as the main topics at this stage. We conducted a user study to evaluate four variants by combining these two elements, and measured the levels of engagement, enjoyment, usability, and memory performance. One of our findings is that there were no differences in the objective results. Combining objective data with observations of the participants’ behavior we provide guidelines as a starting point for the application of the APC framework. Creators need to choose if the viewer will have control over narrative progression and the visibility of interaction based on whether the purpose of a piece is to invoke emotional resonance or promote efficient transfer of knowledge. Also, creators need to consider the viewer’s natural tendency to explore and provide extra incentives to invoke exploratory behaviors in viewers when adding interactive elements. We recommend more viewer control for projects aiming at viewer’s participation and agency, but more director control for projects focusing on education and training. Explicit (vs. implicit) control will also yield higher levels of engagement and enjoyment if the viewer’s uncertainty of interaction consequences can be relieved.

How Ethical Issues Raised by Human–Robot Interaction can Impact the Intention to use the Robot?

The goal of this research is to focus on the ethical issues linked to the interaction between humans and robots in a service delivery context. Through this user study, we want to see how ethics influence user’s intention to use a robot in a frontline service context. We want to observe the importance of each ethical attribute on user’s intention to use the robot in the future. To achieve this goal, we incorporated a video that showed Pepper, the robot, in action. Then respondents had to answer questions about their perception of robots based on the video. Based on a final sample of 341 respondents, we used structural equation modeling (SEM) to test our hypotheses. The results show that the most important ethical issue is the Replacement and its implications for labor. When we look at the impact of the ethical issues on the intention to use, we discovered that the variables impacting the most are Social cues, Trust and Safety.

Patients’, pharmacists’, and prescribers’ attitude toward using blockchain and machine learning in a proposed ePrescription system: online survey

Objective To evaluate the attitudes of the parties involved in the system toward the new features and measure the potential benefits of introducing the use of blockchain and machine learning (ML) to strengthen the in-place methods for safely prescribing medication. The proposed blockchain will strengthen the security and privacy of the patient’s prescription information shared in the network. Once the ePrescription is submitted, it is only available in read-only mode. This will ensure there is no alteration to the ePrescription information after submission. In addition, the blockchain will provide an improved tracking mechanism to ensure the originality of the ePrescription and that a prescriber can only submit an ePrescription with the patient’s authorization. Lastly, before submitting an ePrescription, an ML algorithm will be used to detect any anomalies (eg, missing fields, misplaced information, or wrong dosage) in the ePrescription to ensure the safety of the prescribed medication for the patient. Methods The survey contains questions about the features introduced in the proposed ePrescription system to evaluate the security, privacy, reliability, and availability of the ePrescription information in the system. The study population is comprised of 284 respondents in the patient group, 39 respondents in the pharmacist group, and 27 respondents in the prescriber group, all of whom met the inclusion criteria. The response rate was 80% (226/284) in the patient group, 87% (34/39) in the pharmacist group, and 96% (26/27) in the prescriber group. Key Findings The vast majority of the respondents in all groups had a positive attitude toward the proposed ePrescription system’s security and privacy using blockchain technology, with 72% (163/226) in the patient group, 70.5% (24/34) in the pharmacist group, and 73% (19/26) in the prescriber group. Moreover, the majority of the respondents in the pharmacist (70%, 24/34) and prescriber (85%, 22/26) groups had a positive attitude toward using ML algorithms to generate alerts regarding prescribed medication to enhance the safety of medication prescribing and prevent medication errors. Conclusion Our survey showed that a vast majority of respondents in all groups had positive attitudes toward using blockchain and ML algorithms to safely prescribe medications. However, a need for minor improvements regarding the proposed features was identified, and a post-implementation user study is needed to evaluate the proposed ePrescription system in depth.

Towards a First-Person Perspective Mixed Reality Guidance System for Needle Interventions

While ultrasound (US) guidance has been used during central venous catheterization to reduce complications, including the puncturing of arteries, the rate of such problems remains non-negligible. To further reduce complication rates, mixed-reality systems have been proposed as part of the user interface for such procedures. We demonstrate the use of a surgical navigation system that renders a calibrated US image, and the needle and its trajectory, in a common frame of reference. We compare the effectiveness of this system, whereby images are rendered on a planar monitor and within a head-mounted display (HMD), to the standard-of-care US-only approach, via a phantom-based user study that recruited 31 expert clinicians and 20 medical students. These users performed needle-insertions into a phantom under the three modes of visualization. The success rates were significantly improved under HMD-guidance as compared to US-guidance, for both expert clinicians (94% vs. 70%) and medical students (70% vs. 25%). Users more consistently positioned their needle closer to the center of the vessel’s lumen under HMD-guidance compared to US-guidance. The performance of the clinicians when interacting with this monitor system was comparable to using US-only guidance, with no significant difference being observed across any metrics. The results suggest that the use of an HMD to align the clinician’s visual and motor fields promotes successful needle guidance, highlighting the importance of continued HMD-guidance research.