Breaking the Ice with Group Flow: A Collaborative VR Serious Game for Relationship Enhancement

It is usually hard for unfamiliar partners to rapidly 'break the ice' in the early stage of relationship establishment, which hinders the development of relationship and even affects the team productivity. To solve this problem, we proposed a collaborative serious game for icebreaking by combining immersive virtual reality (VR) with brain-computer interface based on the team flow framework. We designed a multiplayer collaboration task with the theme of fighting COVID-19 and proposed an approach to improve empathy between team members by sharing their real-time mental state in VR;in addition, we propose an EEG-based method for dynamic evaluation and enhancement of group flow experience to achieve better team collaboration. Then, we developed a prototype system and performed a user study. Results show that our method has good ease of use and can significantly reduce the psychological distance among team members. Especially for unfamiliar partners, both functions of mental state sharing and group flow regulation enhancement can significantly reduce the psychological distance. © 2023 IEEE.

Designing an Empathy Training for Depression Prevention Using Virtual Reality and a Preliminary Study

As virtual reality (VR) is labeled by many as 'an ultimate empathy machine,' immersive VR applications have the potential to assist in empathy training for mental healthcare such as depression [21]. In responding to the increasing numbers of diagnosed depression throughout COVID-19, a first-person VR adventure game called 'Schwer' was designed and prototyped by the authors' research team to provide a social support environment for depression treatment. To continue the study and assess the training effectiveness for an appropriate level of empathy, this current article includes a brief survey on data analytics models and features to accumulate evidence for the next phase of the study, an interactive game-level design for the 'Reconstruction' stage, and a preliminary study with data collection. The preliminary study was conducted with a post-game interview to evaluate the design of the levels and their effectiveness in empathy training. Results showed that the game was rated as immersive by all participants. Feedback on the avatar design indicated that two out of three of the non-player characters (NPCs) have made the intended effect. Participants showed mostly positive opinion towards their experienced empathy and provided feedback on innovative teleport mechanism and game interaction. The findings from the literature review and the results of the preliminary study will be used to further improve the existing system and add the data analytics model training. The long-term research goal is to contribute to the healthcare field by developing a dynamic AI-based biofeedback immersive VR system in assisting depression prevention. © 2023 IEEE.

VRChoir: Exploring Remote Choir Rehearsals via Virtual Reality

Choral singing is a creative process that involves continuous, organized, nonverbal communication between conductors and singers. Since the COVID pandemic, choirs are moved to videoconferencing systems for rehearsals. However, the limitation of 2D video interfaces restricts the nonverbal communication, spatial awareness, and sense of presence in choral rehearsal. We designed, implemented, and evaluated VRChoir, a VR-based platform for choir rehearsals to improve these pain points. We evaluated VRChoir with conductors and singers with experience rehearsing in a remote environment. Our findings reveal that VR can be a starting point for improving the sense of presence and quality of non-verbal communication in remote music rehearsals. © 2023 IEEE.

Towards Augmented Reality Guiding Systems: An Engineering Design of an Immersive System for Complex 3D Printing Repair Process

Over the past decade, additive manufacturing (AM) has become widely adopted for both prototyping and, more recently, end-use products. In particular, fused deposition modeling (FDM) is the most widespread form of additive manufacturing due to its low cost, ease of use, and versatility. While additive processes are relatively automated, many steps in their operation and repair require trained human operators. Finding such operators can be difficult, as highlighted during the recent COVID-19 pandemic. Augmented reality (AR) systems could significantly help address this challenge by automating the training for 3D printer operators. Given multidimensional design choices, however, a research gap exists in the system requirements for such immersive guidance. To address this need, we explore the applicability of AR to guide users through a repair process. In that context, we report on the system design as well as the results of the AR system assessment in a qualitative study with experts. © 2023 IEEE.

Can You Smell Me Now: Towards a Remote Olfactory Study

The sense of smell-olfaction involves the natural processing of ambient information in real-time. This process allows humans to detect danger, identify familiarities, and form lasting memories. During the COVID-19 pandemic, researchers were presented with challenges related to conducting in-person olfactory-based user studies. In this paper, we explore user experience and perception during olfactory-based interactions (OBI). Based upon previous literature, we propose an approach to offer future researchers a methodology for conducting olfactory-based user studies remotely. In particular, we explored a paper prototyping medium as an olfactory display. This experiment demonstrates the remote investigation of a complex sensory functionality during high mental work-load levels while participants (N=12) engage in an online memory game. Furthermore, this work seeks to inspire further discussion of olfactory-based user studies that explore functions related to human moods, memory, and behavior.

Using an Immersive Video Environment to Assess Pedestrians' Compliance With COVID Distance Keeping Interventions

Physical distancing is a key measure to slow the spread of many highly infectious diseases, e.g. COVID-19. Streetscape interventions such as pedestrian signage can contribute to ensuring distances are kept, but it is unclear to what extent people comply with these in practice. This paper tackles this question using an immersive video environment to realistically simulate real-life streetscapes in the lab. In a controlled user study, we augmented panoramic video footage with pedestrian one-way street signage and recorded route decisions to assess compliance with distance keeping measures. Our results indicate that such signage affects routing decisions and can thus help pedestrians to avoid crowded situations where distance keeping is difficult. We also identified further factors affecting decisions and a correlation between intention to comply and actual compliance. The experimental method we used enabled us to effectively and safely carry out a study of a phenomenon that in the real world depends on interaction with the physical environment. This method may have applications in other areas in which simulations of physical environments are important.

Techniques for using VRChat to Replace On-site Experiments

In this paper, we present a technique to conduct on-site laboratory experiments using VRChat, a social Virtual Reality platform. COVID-19 pandemic has created challenges and restrictions on re-searchers in running experiments for Human-Computer Interaction research. Hence, universities and institutions set guidelines for social distancing and encourage people to work from home. Therefore, participants are harder to recruit for experiments that run in a physical laboratory. Our technique uses VRChat as a substitution for running on-site experiments despite social restrictions. We exploit features in VRChat to enable researchers to run experiments with domestically recruited participants. Furthermore, we propose a hassle-free method to retrieve study data. This paper also discusses and offers design considerations to run an on-site experiment using VRChat over a homemade system. © 2022 IEEE.

Virtual Reality Therapy for the Psychological Well-being of Palliative Care Patients in Hong Kong

In this paper we introduce novel Virtual Reality (VR) and Aug-mented Reality (AR) treatments to improve the psychological well being of patients in palliative care, based on interviews with a clin-ical psychologist who has successfully implemented VR assisted interventions on palliative care patients in the Hong Kong hospital system. Our VR and AR assisted interventions are adaptations of traditional palliative care therapies which simultaneously facilitate patients communication with family and friends while isolated in hospital due to physical weakness and COVID-19 related restrictions. The first system we propose is a networked, metaverse platform for palliative care patients to create customized virtual environments with therapists, family and friends which function as immersive and collaborative versions of 'life review' and 'reminiscence therapy'. The second proposed system will investigate the use of Mixed Real-ity telepresence and haptic touch in an AR environment, which will allow palliative care patients to physically feel friends and family in a virtual space, adding to the sense of presence and immersion in that environment. © 2022 IEEE.

Accelerating the Front End of Medicine: Three Digital Use Cases and HCI Implications.

Digital applications in health care are a concurrent research and management question, where implementation experiences are a core field of information systems research. It also contributes to fighting pandemic crises like COVID-19 because contactless information flow and speed of diagnostics are improved. This paper presents three digital application case studies from emergency medicine, administration management, and cancer diagnosis with AI support from the University Medical Centers of Münster and Göttingen in Germany. All cases highlight the potential of digitalization to increase speed and efficiency within the front end of medicine as the crucial phase before patient treatment starts. General challenges for health care project implementations and human-computer interaction (HCI) concepts in health care are derived and discussed, including the importance of specific processes together with user analysis and adaption. A derived concept for HCI includes the criteria speed, accuracy, modularity, and individuality to achieve sustainable improvements within the front end of medicine.

A study of redesigning food delivery application in Thailand

User interface (UI) and user experience (UX) design is fundamental to the stickiness of any application. Food delivery is no exception. With the food delivery business sector on the rise during the coronavirus disease 2019 (COVID-19) pandemic, it is necessary for any newcomers in the market to at least match the must-have feature lists of the major players. However, Robinhood, despite having a niche in societal responsibility, is still a food delivery app that is found to lack some of the features that, in the past few months, due to the fierce competition within the food delivery space, moved down from a delighter to a must-have. In this paper, we show, through iterations of qualitative interviews, the proposed solutions consisting of features and future roadmap along with the general context of why each implementation was selected in each sprint. Through all these experiments, we learned not to go against the natural reading pattern of reading from left to right, the z pattern in the visual hierarchy, the users’ familiarity with buttons placement due to loaded external factors, and how introducing too many new features may negatively impact the usability test score © This is an open access article under the CC BY-SA license

The Effect of Virtual Humans Making Verbal Communication Mistakes on Learners' Perspectives of their Credibility, Reliability, and Trustworthiness

Simulating real-world experiences in a safe environment has made virtual human medical simulations a common use case for research and interpersonal communication training. Despite the benefits virtual human medical simulations provide, previous work suggests that users struggle to notice when virtual humans make potentially life-threatening verbal communication mistakes inside virtual human medical simulations. In this work, we performed a 2x2 mixed design user study that had learners (n = 80) attempt to identify verbal communication mistakes made by a virtual human acting as a nurse in a virtual desktop environment. A virtual desktop environment was used instead of a head-mounted virtual reality environment due to Covid-19 limitations. The virtual desktop environment experience allowed us to explore how frequently learners identify verbal communication mistakes in virtual human medical simulations and how perceptions of credibility, reliability, and trustworthiness in the virtual human affect learner error recognition rates. We found that learners struggle to identify infrequent virtual human verbal communication mistakes. Additionally, learners with lower initial trustworthiness ratings are more likely to overlook potentially life-threatening mistakes, and virtual human mistakes temporarily lower learner credibility, reliability, and trustworthiness ratings of virtual humans. From these findings, we provide insights on improving virtual human medical simulation design. Developers can use these insights to design virtual simulations for error identification training using virtual humans.

VR Training: The Unused Opportunity to Save Lives During a Pandemic

When on life support, the patients' lives not only depend on the availability of the medical devices but also on the staff's expertise to use them. With the example of ECMO devices, which were highly demanded during the COVID-19 pandemic but rarely used until then, we developed a VR training for priming an ECMO to provide the required expertise in a standardized and simple way on a global scale. This paper presents the development of VR training with feedback from medical and technical experts.

A Cardboard-Based Virtual Reality Study on Self-Avatar Appearance and Breathing

Cardboard-based virtual reality is an affordable solution for experiencing virtual reality content. Particularly during the COVID-19 pandemic, several studies used cardboard-based virtual reality remotely to minimize viral spread. We conducted a study to explore the potentials of low-cost virtual reality on participants' sense of presence and body ownership illusion in our research lab, thereby providing a controlled research setting. Our 2 (Avatar: realistic vs. mannequin self-avatar) x 2 (Breathing;breathing vs. no breathing motion) study investigated presence and body ownership when participants were instructed to observe a virtual environment passively through a cardboard-based virtual reality application while being embodied as a self-avatar. Our study's results indicated that: (1) the mannequin self-avatar exerted a stronger effect on participants' presence;(2) younger participants who experienced the mannequin avatar reported stronger body ownership compared with older participants;and (3) while experiencing a mannequin avatar with no breathing motion, participants with prior VR experience reported higher body ownership illusion compared with participants with no prior VR experience. In this paper, we discuss our findings, as well as the study's limitations and future research directions.

Can You Smell Me Now: Toward s a Remote Olfactory Study

The sense of smell-olfaction involves the natural processing of ambient information in real-Time. This process allows humans to detect danger, identify familiarities, and form lasting memories. During the COVID-19 pandemic, researchers were presented with challenges related to conducting in-person olfactory-based user studies. In this paper, we explore user experience and perception during olfactory-based interactions (OBI). Based upon previous literature, we propose an approach to offer future researchers a methodology for conducting olfactory-based user studies remotely. In particular, we explored a paper prototyping medium as an olfactory display. This experiment demonstrates the remote investigation of a complex sensory functionality during high mental workload levels while participants (N=12) engage in an online memory game. Furthermore, this work seeks to inspire further discussion of olfactory-based user studies that explore functions related to human moods, memory, and behavior. © 2022 ACM.

AiR: An Augmented Reality Application for Visualizing Air Pollution

In order to effectively combat Air Pollution, it is necessary for the government and the community to work together. Easily comprehensible visualizations can play a major role in drawing public attention and spreading awareness about seemingly intangible air pollution. Considering the widespread usage of Android-based devices, in this paper, we propose an Augmented Reality based application called AiR, to help users to visualize pollutants in the air and to create an immersive user experience. It aims to interactively engage a wide variety of users and create awareness without overwhelming them with data. AiR visualizes 12 pollutants [PM10, PM2.5, NO, NO2, NOx, CO, SO2,O-3,NH3, C6H6, (CH3)C6H5 and (CH3)(2)C6H5] through unique models. We demonstrate our application on pollution data by CPCB from various weather stations across India collected over the initial lockdown period due to COVID-19 in India.

COVID-19 EnsembleVis: Visual Analysis of County-level Ensemble Forecast Models

The spread of the SARS-CoV-2 virus and its contagious disease COVID-19 has impacted countries to an extent not seen since the 1918 flu pandemic. In the absence of an effective vaccine and as cases surge worldwide, governments were forced to adopt measures to inhibit the spread of the disease. To reduce its impact and to guide policy planning and resource allocation, researchers have been developing models to forecast the infectious disease. Ensemble models, by aggregating forecasts from multiple individual models, have been shown to be a useful forecasting method. However, these models can still provide less-than-adequate forecasts at higher spatial resolutions. In this paper, we built COVID-19 EnsembleVis, a web-based interactive visual interface that allows the assessment of the errors of ensembles and individual models by enabling users to effortlessly navigate through and compare the outputs of models considering their space and time dimensions. COVID-19 EnsembleVis enables a more detailed understanding of uncertainty and the range of forecasts generated by individual models.

Should I Follow this Model? The Effect of Uncertainty Visualization on the Acceptance of Time Series Forecasts

Time series forecasts are ubiquitous, ranging from daily weather forecasts to projections of pandemics such as COVID-19. Communicating the uncertainty associated with such forecasts is important, because it may affect users' trust in a forecasting model and, in turn, the decisions made based on the model. Although there exists a growing body of research on visualizing uncertainty in general, the important case of visualizing prediction uncertainty in time series forecasting is under-researched. Against this background, we investigated how different visualizations of predictive uncertainty affect the extent to which people follow predictions of a time series forecasting model. More specifically, we conducted an online experiment on forecasting occupied hospital beds due to the COVID-19 pandemic, measuring the influence of uncertainty visualization of algorithmic predictions on participants' own predictions. In contrast to prior studies, our empirical results suggest that more salient visualizations of uncertainty lead to decreased willingness to follow algorithmic forecasts.

Socially Distanced: Have user evaluation methods for Immersive Technologies changed during the COVID-19 pandemic?

Since the emergence of COVID-19 in late 2019, there has been a significant disturbance in human-to-human interaction that has changed the way we conduct user studies in the field of Human-Computer Interaction (HCI), especially for extended (augmented, mixed, and virtual) reality (XR). To uncover how XR research has adapted throughout the pandemic, this paper presents a review of user study methodology adaptations from a corpus of 951 papers. This corpus of papers covers CORE 2021 A* published conference submissions, from Q2 2020 through to Q1 2021 (IEEE ISMAR, ACM CHI, IEEE VR). The review highlights how methodologies were changed and reported;sparking discussions surrounding how methods should be conveyed and to what extent research should be contextualised, by drawing on external topical factors such as COVID-19, to maximise usefulness and perspective for future studies. We provide a set of initial guidelines based on our findings, posing key considerations for researchers when reporting on user studies during uncertain and unprecedented times.

Supporting Remote Survey Data Analysis by Co-researchers with Learning Disabilities through Inclusive and Creative Practices and Data Science Approaches.

Through a process of robust co-design, we created a bespoke accessible survey platform to explore the role of co-researchers with learning disabilities (LDs) in research design and analysis. A team of co-researchers used this system to create an online survey to challenge public understanding of LDs [3]. Here, we describe and evaluate the process of remotely co-analyzing the survey data across 30 meetings in a research team consisting of academics and non-academics with diverse abilities amid new COVID-19 lockdown challenges. Based on survey data with >1,500 responses, we first co-analyzed demographics using graphs and art & design approaches. Next, co-researchers co-analyzed the output of machine learning-based structural topic modelling (STM) applied to open-ended text responses. We derived an efficient five-steps STM co-analysis process for creative, inclusive, and critical engagement of data by co-researchers. Co-researchers observed that by trying to understand and impact public opinion, their own perspectives also changed.

Expression and purification of tag-free SARS-CoV-2 RNA-dependent RNA polymerase in Escherichia coli.

The RNA-dependent-RNA polymerase (RdRp) from SARS-CoV-2 is an important drug target because it is responsible for viral RNA genome replication. Efficient production of recombinant RdRp is important in screening antivirals to treat COVID-19. Here, we present our protocol for expression of tag-free replication complex proteins in E. coli and subsequent purification. Despite the added complexity of multiple purification steps, our methods provide greater activity, yield at lower cost, and are faster than baculovirus expression systems. For complete details on the use and execution of this protocol, please refer to Dangerfield et al. (2020).