Miracle-dz/UniFAR-FTUs huggingface dataset:
Emoband: Investigating the Affective Perception towards On-wrist Stroking and Squeezing Feedback mediated by Different Textile Materials

This paper investigates how different textile materials on the wrist bands may mediate the affective experience of two forms of tactile icons, namely stroking and squeezing. To this end, we designed Emoband, a wrist-worn textile-based tactile display that can stroke or squeeze on wearers’ wrists through the moving fabrics. We conducted two studies on the participants’ valence and arousal ratings towards the stroking and squeezing feedback from Emoband, respectively. Results showed that the valence ratings were significantly affected by the stroking or squeezing parameters and the wristband’s material, interactively. The movement-related parameters dominated the arousal rating. Meanwhile, the valence ratings demonstrated different tendencies between the two tactile feedback, with the valence increasing and decreasing along with the strength of stroking and squeezing, respectively. Besides, the valence ratings of the stroking stimuli demonstrated varied distributions across different materials, indicating the materials’ varying affective expressiveness in the wrist-worn haptic devices.
FlowAR: How Different Augmented Reality Visualizations of Online Fitness Videos Support Flow for At-Home Yoga Exercises

Online fitness video tutorials are an increasingly popular way to stay fit at home without a personal trainer. However, to keep the screen playing the video in view, users typically disrupt their balance and break the motion flow — two main pillars for the correct execution of yoga poses. While past research partially addressed this problem, these approaches supported only a limited view of the instructor and simple movements. To enable the fluid execution of complex full-body yoga exercises, we propose FlowAR, an augmented reality system for home workouts that shows training video tutorials as always-present virtual static and dynamic overlays around the user. We tested different overlay layouts in a study with 16 participants, using motion capture equipment for baseline performance. Then, we iterated the prototype and tested it in a furnished lab simulating home settings with 12 users. Our results highlight the advantages of different visualizations and the system’s general applicability.
IntimaSea: Exploring Shared Stress Display in Close Relationships

Automatic stress tracking has become increasingly available on wearable devices. Research has investigated its use for individual stress management, largely within the traditional data-as-care framing. However, its use for stress sharing in social relationships, particularly close relationships, is still under explored. Inspired by the idea of “caring-through-data”, which focuses on mediating the social and emotional experiences of the collective “us” with data, this paper presents a design study with a prototype called IntimaSea, a display featuring illustrative stress data in collective forms to be shared among close relationships. The field trials with nine groups of intimately-connected users (N=19) highlight its potential on stress awareness, interpretation and management, as well as intimacy promotion. We end by discussing sharing stress for social ways of stress management, stress data as a meaningful social cue mediating relationships, as well as design implications for caring-through-data.
Building Positively Affective Location-Based Advertising: A Study of Pokémon GO Players

With the expanding popularity of Location-Based Games and the rise of advertising therein, there exists a need to comprehend the impact of Location-Based Game Advertising (LGA). This paper seeks to identify what makes positively affective LGA, leveraging Pokémon GO as a probe. Researchers conducted twenty-seven (n=27) semi-structured interviews with Pokémon GO players to reveal lived experiences regarding LGA. Our findings highlight the following direct implications for LGA: (1) LGA act as a digital billboard, conveying qualitative alongside locative information, and (2) well-received LGA enhances the player’s agency. We additionally identify findings that have auxiliary implications to LGA: (3) positive memorability occurs when points of interest match physical reality, and (4) ludic engagement is a mediating factor in the memorability of locations. This research demonstrates that LGA in Location-Based Games is surprisingly well-received. However, developers must provide extra consideration to the player’s agency for such techniques to be effective.
Minimizing change aversion through mixed methods research: a case study of redesigning Spotify’s Your Library

Launching a radical change to a habitual feature, used by millions every day, presents a challenge both to the end user and the organization making the change. Change aversion to habitually used features is a known factor in users experience design, but at times major changes are needed to encompass feature growth ultimately benefiting users. In this case study, we present examples of how data science and user research collaborated during the redesign the mobile Library feature at Spotify. Major adaptions were needed in order to enable future opportunities. The challenge required a high degree of sensitivity to users’ needs within what is often considered their space in the world of streaming. We believe that close collaboration between the product, design, engineering, data science, and user research disciplines, with a focus on quantitative and qualitative mixed methods insight work in early development phases, enabled the experience to be launched with the users’ experience at the forefront and thus minimising change aversion.
AI Shall Have No Dominion: on How to Measure Technology Dominance in AI-supported Human decision-making

In this article, we propose a conceptual and methodological framework for measuring the impact of the introduction of AI systems in decision settings, based on the concept of technological dominance, i.e. the influence that an AI system can exert on human judgment and decisions. We distinguish between a negative component of dominance (automation bias) and a positive one (algorithm appreciation) by focusing on and systematizing the patterns of interaction between human judgment and AI support, or reliance patterns, and their associated cognitive effects. We then define statistical approaches for measuring these dimensions of dominance, as well as corresponding qualitative visualizations. By reporting about four medical case studies, we illustrate how the proposed methods can be used to inform assessments of dominance and of related cognitive biases in real-world settings. Our study lays the groundwork for future investigations into the effects of introducing AI support into naturalistic and collaborative decision-making.
The Perceived Utility of Smartphone and Wearable Sensor Data in Digital Self-tracking Technologies for Mental Health

Mental health symptoms are commonly discovered in primary care. Yet, these settings are not set up to provide psychological treatment. Digital interventions can play a crucial role in stepped care management of patients’ symptoms where patients are offered a low intensity intervention, and treatment evolves to incorporate providers if needed. Though digital interventions often use smartphone and wearable sensor data, little is known about patients’ desires to use these data to manage mental health symptoms. In 10 interviews with patients with symptoms of depression and anxiety, we explored their: symptom self-management, current and desired use of sensor data, and comfort sharing such data with providers. Findings support the use digital interventions to manage mental health, yet they also highlight a misalignment in patient needs and current efforts to use sensors. We outline considerations for future research, including extending design thinking to wraparound services that may be necessary to truly reduce healthcare burden.
Faulty or Ready? Handling Failures in Deep-Learning Computer Vision Models until Deployment: A Study of Practices, Challenges, and Needs

Handling failures in computer vision systems that rely on deep learning models remains a challenge. While an increasing number of methods for bug identification and correction are proposed, little is known about how practitioners actually search for failures in these models. We perform an empirical study to understand the goals and needs of practitioners, the workflows and artifacts they use, and the challenges and limitations in their process. We interview 18 practitioners by probing them with a carefully crafted failure handling scenario. We observe that there is a great diversity of failure handling workflows in which cooperations are often necessary, that practitioners overlook certain types of failures and bugs, and that they generally do not rely on potentially relevant approaches and tools originally stemming from research. These insights allow to draw a list of research opportunities, such as creating a library of best practices and more representative formalisations of practitioners’ goals, developing interfaces to exploit failure handling artifacts, as well as providing specialized training.
Don’t Panic! - Influence of Virtual Stressor Representations from the ICU Context on Perceived Stress Levels

Intensive care nurses are prone to suffering from chronic stress due to constant exposure to two main profession-related stressors: interruption and time pressure. These stressors have detrimental effects on the well-being of the nursing staff and, by proxy, the patients. To alleviate stress, increase safety, and support the training of stressful scenarios, we investigate the impact these stressors have on subjective and objective stress levels in a virtual environment. We designed an intensive care unit in which participants (n=26, 18 healthcare professionals) perform common tasks, e.g. refilling an infusion pump, whilst being exposed to interruptions and time pressure. Results from our between-subjects study provide data indicating stress increase in both stressor conditions, suggesting that artificially evoking work-related stressors for stress inoculation training (SIT) is a possible extension to simulation training during nursing education. This knowledge is helpful for designing training scenarios of safety-critical situations early in the professional apprenticeship.
Action Translate: Supporting Students in Translation Volunteering

University students are well known for volunteering within non-governmental organisations (NGOs). A significant part of NGO practice is the production of documents that communicate their work to local communities and international stakeholders. However, organisations often struggle to resource translations of these documents, resulting in the exclusion of the very same communities that they want to reach. Although many students are multilingual and are willing to volunteer their time and language skills, there are few structured opportunities configured for such non-professional translation of content in the short-term mode that would fit into the student pattern of availability. We developed Action Translate to specifically support these motivated, non-professional translators within the volunteering constraints of university life. Action Translate leverages machine translation post-editing to support teams of volunteers working on NGO translation projects online. Through analysis of a real-world deployment, we discuss how digital systems can be developed to better support student volunteer translators, specifically in building collegiate interaction and identity as translators for a cause.
Investigating Eyes-away Mid-air Typing in Virtual Reality using Squeeze haptics-based Postural Reinforcement

In this paper, we investigate postural reinforcement haptics for mid-air typing using squeeze actuation on the wrist. We propose and validate eye-tracking based objective metrics that capture the impact of haptics on the user’s experience, which traditional performance metrics like speed and accuracy are not able to capture. To this end, we design four wrist-based haptic feedback conditions: no haptics, vibrations on keypress, squeeze+vibrations on keypress, and squeeze posture reinforcement + vibrations on keypress. We conduct a text input study with 48 participants to compare the four conditions on typing and gaze metrics. Our results show that for expert qwerty users, posture reinforcement haptics significantly benefit typing by reducing the visual attention on the keyboard by up to 44% relative to no haptics, thus enabling eyes-away behaviors.
Local Circulations Developed in the Vicinity of Both Coastal and Inland Urban Areas. Part II: Effects of Urban and Mountain Areas on Moisture Transport

The moisture distribution near the ground surface in and around the Japanese cities of Osaka and Kyoto was investigated. From the analysis of observed data, the atmosphere over the suburban areas between coastal Osaka and inland Kyoto was drier than that over Osaka and Kyoto during the daytime hours. This feature differs from results in previous studies and from expectations based on urban and suburban surface heat budgets. To understand the drying mechanism, numerical experiments were performed, using a simplified geometrical model consisting of a straight coastline, a square urban area on the coast, a square inland urban area, and a plateau mountain surrounding the urban areas. The following main results were obtained. First, suburban drying during the daytime was mainly caused by a valley circulation that developed over the surrounding mountain area. In addition, the two heat island circulations that developed over the two urban areas also caused suburban drying. As a consequence, the coexistence of mountain and urban areas caused more notable suburban drying. Second, the amount of suburban drying was greatest when the urban distance was 40‐50 km, which is roughly equal to the actual distance between the Osaka and Kyoto urban areas. Last, temporal changes in moisture and those of suspended particulate matter, SO 2, and NOx concentrations decreased before the arrival of the sea-breeze front. Thus, it is argued that moisture and pollutants were transported by the two heat island circulations that developed over Osaka and Kyoto and by the valley circulations and then were modified by the sea-breeze circulation.
Measuring and Understanding Trust Calibrations for Automated Systems: A Survey of the State-Of-The-Art and Future Directions

Trust has been recognized as a central variable to explain the resistance to using automated systems (under-trust) and the overreliance on automated systems (over-trust). To achieve appropriate reliance, users’ trust should be calibrated to reflect a system’s capabilities. Studies from various disciplines have examined different interventions to attain such trust calibration. Based on a literature body of 1000+ papers, we identified 96 relevant publications which aimed to calibrate users’ trust in automated systems. To provide an in-depth overview of the state-of-the-art, we reviewed and summarized measurements of the trust calibration, interventions, and results of these efforts. For the numerous promising calibration interventions, we extract common design choices and structure these into four dimensions of trust calibration interventions to guide future studies. Our findings indicate that the measurement of the trust calibration often limits the interpretation of the effects of different interventions. We suggest future directions for this problem.
The bivariate dispersion control charts for non-normal processes

This article study the performance of the bivariate dispersion control charts, namely the and the charts, for the bivariate normal, bivariate exponential, bivariate t(5), bivariate Logistic and bivariate Laplace distributions. The asymmetrical probability limits of these charts are proposed for the distributions under study. The estimated factors and quantile points used in the construction of these two charts are provided for the bivariate non-normal distributions. The effect of improper use of constants and quantile points in the construction of the and the charts are studied in terms of the associated false alarm rates. The performances of the proposed limits of the given charts are evaluated in terms of average run length for the various bivariate distributions and compared. The performances of these control charts are also compared with their respective 3σ limits.
Watch Out for Updates: Understanding the Effects of Model Explanation Updates in AI-Assisted Decision Making

AI explanations have been increasingly used to help people better utilize AI recommendations in AI-assisted decision making. While AI explanations may change over time due to updates of the AI model, little is known about how these changes may affect people’s perceptions and usage of the model. In this paper, we study how varying levels of similarity between the AI explanations before and after a model update affects people’s trust in and satisfaction with the AI model. We conduct randomized human-subject experiments on two decision making contexts where people have different levels of domain knowledge. Our results show that changes in AI explanation during the model update do not affect people’s tendency to adopt AI recommendations. However, they may change people’s subjective trust in and satisfaction with the AI model via changing both their perceived model accuracy and perceived consistency of AI explanations with their prior knowledge.
Partially Blended Realities: Aligning Dissimilar Spaces for Distributed Mixed Reality Meetings

Mixed Reality allows for distributed meetings where people’s local physical spaces are virtually aligned into blended interaction spaces. In many cases, people’s physical rooms are dissimilar, making it challenging to design a coherent blended space. We introduce the concept of Partially Blended Realities (PBR) — using Mixed Reality to support remote collaborators in partially aligning their physical spaces. As physical surfaces are central in collaborative work, PBR supports users in transitioning between different configurations of tables and whiteboard surfaces. In this paper, we 1) describe the design space of PBR, 2) present RealityBlender to explore interaction techniques for how users may configure and transition between blended spaces, and 3) provide insights from a study on how users experience transitions in a remote collaboration task. With this work, we demonstrate new potential for using partial solutions to tackle the alignment problem of dissimilar spaces in distributed Mixed Reality meetings.
Exploring the digital support needs of caregivers of people with serious mental illness

In low-and middle-income countries like India, people with severe mental illness (PSMI) rely on their families as a primary source of care, given the lack of support from healthcare systems. The demanding nature of caregiving places significant physical and mental demands on caregivers, who are the primary source of support to PSMI. We explore how caregivers in under-resourced settings can be better supported through everyday digital technologies. We conducted interviews with caregivers (from urban and rural India), as well as workshops with professionals from Indian NGOs that work directly with PSMIs. We found that technology has the potential to (1) provide carer-centred support that empowers carers who experience stigma and issues with existing support networks; (2) provide support for carers to overcome barriers and progress in the recovery of the PSMI. We conclude with design considerations, proposing how an online peer community can leverage carers’ expertise to actualise support provision.
Focused Time Saves Nine: Evaluating Computer–Assisted Protected Time for Hybrid Information Work

Information workers often struggle to balance their time for a variety of activities like focused work, communication, and caring. This study analyzes the impact of a commercially available computer-assisted time protection intervention that automatically and preemptively schedules calendar time for self-determined activities. We analyzed the behaviors and self-reports of workers in two naturalistic studies. First, we studied 27 workers who were already using Computer-Assisted Protected Time (CAP time) and found that they mainly used it for focused work. Second, we analyzed the effect of CAP time as a randomized intervention on 89 workers who never had CAP time and found that those with it self-reported an increase in performance, job resources, and immersion. In both studies, workers with CAP time exhibited a rearrangement of activities leading to an overall reduction in work activity. This study highlights new opportunities for intelligent time-management interventions and the importance of protected time at work.
‘You are you and the app. There’s nobody else.’: Building Worker-Designed Data Institutions within Platform Hegemony

Information asymmetries create extractive, often harmful relationships between platform workers (e.g., Uber or Deliveroo drivers) and their algorithmic managers. Recent HCI studies have put forward more equitable platform designs but leave open questions about the social and technical infrastructures required to support them without the cooperation of platforms. We conducted a participatory design study in which platform workers deconstructed and re-imagined Uber’s schema for driver data. We analyzed the data structures and social institutions participants proposed, focusing on the stakeholders, roles, and strategies for mitigating conflicting interests of privacy, personal agency, and utility. Using critical theory, we reflected on the capability of participatory design to generate bottom-up collective data infrastructures. Based on the plurality of alternative institutions participants produced and their aptitude to navigate data stewardship decisions, we propose user-configurable tools for lightweight data institution building, as an alternative to redesigning existing platforms or delegating control to centralized trusts.
“We Need a Big Revolution in Email Advertising”: Users’ Perception of Persuasion in Permission-based Advertising Emails

Persuasive tactics intend to encourage users to open advertising emails. However, these tactics can overwhelm users, which makes them frustrated and leads to lower open rates. This paper intends to understand which persuasive tactics are used and how they are perceived by users. We first developed a categorization of inbox-level persuasive tactics in permission-based advertising emails. We then asked participants to interact with an email inbox prototype, combined with interviews (N=32), to investigate their opinions towards advertising emails and underlying persuasive tactics. Our qualitative findings reveal poor user experience with advertising emails, which was related to feeling surveilled by companies, forced subscription, high prior knowledge about persuasive tactics, and a desire for more agency. We also found that using certain persuasive tactics on the inbox level is perceived as ethically inappropriate. Based on these insights, we provide design recommendations to improve advertising communication and make such emails more valuable to users.