What if we deliberately designed computers to be creepy? This pictorial explores using Design Fiction to create a collection of speculative creepy devices that we could imagine living with. We investigated how leveraging creepiness as a normalised design attribute could serve as a resource to reflect on what makes good user-centred design. During a span of nine weeks, we engaged in sharing our personal lived experiences as a prompt to imagine creepy futures and devices that could address our needs, albeit designed to be creepy. This approach enabled us to evoke experiences that have not happened with devices that do not exist, which facilitated a reflection on their impact on everyday choreographies and tensions on their usability through speculative autoethnographies. We contribute a set of imaginary devices from creepy futures that illustrate the exploration and adoption of creepy speculations to facilitate new critical discourses to rethink designing interactive systems.

As Pakistan’s population ages and traditional care structures evolve, there is increasing interest in technological solutions for supporting older adults at home. This study investigates the potential of social assistive robots (SARs) in Pakistani homes, focusing on cultural values, inter-generational living, and limited access to such technologies. In a 3-day mixed-methods home study, 14 older adults interacted with a SAR communicating in Urdu. Through observations, interviews, and questionnaires, we evaluated the robot’s acceptability, engagement, and cultural compatibility. The results highlighted the need for culturally sensitive design, emphasising the role of robots as companions rather than replacements for human care, and the importance of robot’s ability to communicate in Urdu. We discuss how SARs could be designed to reflect the characteristics of Pakistani households, including faith, family values, everyday routines, and environmental factors. Our design considerations can benefit research on deploying SARs to support older adults in Pakistan and similar cultures.

Encouraging home-based physical activity (PA) is increasingly important for public health. While smartphones and smartwatches are widely adopted, passive monitoring fails to effectively promote home exercise, providing basic metrics without meaningful feedback or user-preference alignment. Recent technological advances enable interactive, tangible devices designed for home PA interventions. We systematically reviewed 21 studies published since 2015 describing functional devices with physical components designed for stand-alone home use to analyse device categories, modalities, feedback mechanisms, and behaviour change techniques (BCTs). Our findings show a dominance of embedded systems that support strength and balance activities, visual-heavy feedback, limited layering of triggers, and a limited use of BCTs directly linked to habit formation. We offer design directions for tangible devices that support PA in home environments and promote durable behaviour change through emphasising stationary aerobic micro routines, layering prompts embedded in objects, and providing a mix of real-time and delayed feedback.

Advances in digital fabrication with flexible and conductive materials are enabling new opportunities for customisable wearables that enhance physical training across various sports through on-body posture and movement monitoring.However, before developing new wearable devices, it is crucial to understand the unique challenges and opportunities of real-world use and the diverse needs of stakeholders such as athletes, trainers, and sports enthusiasts.In this paper, we report results of two co-design workshops conducted with 11 participants representing a range of sports backgrounds and interests to identify challenges and opportunities for flexible wearables.The participants' designs and prototypes highlight the importance of supporting personalised wearable design, addressing varying contexts, and accommodating different skill levels.We propose design considerations for wearable devices that prioritise flexibility, both in their materiality to support a wide range of movement and in their adaptability to accommodate changing conditions and user progression across skill levels.

Bossware, software that monitors worker activity, is a common feature of workplaces. What do workers know about these tools and how they relate to their rights at work? We explored this question through two studies. Study 1 surveyed 100 workers to assess their understanding of work monitoring terminology. Participants were confident in their knowledge of key terms but struggled to accurately define them. Study 2 explored awareness of legal protection in relation to work monitoring through 19 semi-structured online interviews. We found that awareness varied with industry and work role, but was generally low and lacked certainty. Participants were largely skeptical of the use of bossware, questioning its necessity. Limited knowledge of monitoring terminology and legal protection at work further weakens workers' ability to notice and challenge the use of monitoring tools in their workplaces. We finish by speculating on whether educating workers about bossware and workplace rights would help.

As robots are increasingly becoming part of daily life worldwide, it is important to ensure that they are inclusive and culturally sensitive to accommodate users from different backgrounds. In particular, many countries in the Global South (GS) have yet to explore the integration and benefits of robots, especially for underrepresented language groups such as Urdu. We present an exploratory mixed-methods study that investigates how robots' language affects the social interaction, acceptability and overall perception of robots within Pakistani Urdu-speaking individuals. The findings highlight the importance of language and cultural adaptation, and how these factors influence the acceptance of robots, emphasising the need for more inclusive and religion sensitive technologies designed for the GS users.

Designing positive robot experiences requires an understanding of users' perceptions and meeting their needs in an ethical manner. However, despite best intentions, users have strong positive or negative reactions to robots, either finding them “cute“ or “creepy”. The Perceived Creepiness of Technology Scale (PCTS) was designed for evaluating how creepy a technology appears to a user on first encounter. In this paper we applied the PCTS to a cross-section of social robots to measure their perceived creepiness and evaluate the strengths and weaknesses of PCTS when applied in a Human-Robot Interaction (HRI) context. We demonstrate that while a robot may not be perceived as creepy initially, it can have underlying unethical practices inherent in its design which is not well captured by the PCTS. This emphasises the need for better HRI practices to ensure creepiness is appropriately assessed in the social robot domain.

Human Action Quality Assessment (AQA), which aims to automatically evaluate the performance of actions executed by humans, is an emerging field of human action analysis. Although many review articles have been conducted for human action analysis fields such as action recognition and action prediction, there is a lack of up-to-date and systematic reviews related to AQA. This paper aims to provide a systematic literature review of existing papers on vision-based human AQA. This systematic review was rigorously conducted following the PRISMA guideline through the databases of Scopus , IEEE Xplore, and Web of Science in July 2024. Ninety-six research articles were selected for the final analysis after applying inclusion and exclusion criteria. This review presents an overview of various aspects of AQA, including existing applications, data acquisition methods, public datasets, state-of-the-art methods and evaluation metrics . We observe an increase in the number of studies in AQA since 2019, primarily due to the advent of deep learning methods and motion capture devices. We categorize these AQA methods into skeleton-based and video-based methods based on the data modality used. There are different evaluation metrics for various AQA tasks. SRC is the most commonly used evaluation metric, with fifty-six out of ninety-six selected papers using it to evaluate their models. Sports event scoring, surgical skill evaluation and rehabilitation assessment are the most popular three scenarios in this direction based on existing papers and there are more new scenarios being explored such as piano skill assessment. Furthermore, the existing challenges and future research directions are provided, which can be a helpful guide for researchers to explore AQA.

Research indicates that a significant number of individuals are in a suboptimal auditory health state , yet their auditory function can potentially be improved through auditory training. To raise awareness of auditory health issues, auditory training apps should provide effective yet accessible training methods alongside engaging mechanisms that motivate users to adopt and sustain auditory training habits, ultimately facilitating self-directed auditory health management. Current auditory training apps overlook the importance of user needs and motivation, as well as the relationship between the two, leading to low engagement and retention rates. We document the specific needs of both normal-hearing and mildly hearing-impaired users and analyze physiological data collected during auditory training tasks. Through lab experiment study, we provide quantitative evidence supporting the effectiveness of the auditory training method used in this study. The findings indicate that audiovisual-based auditory training contributes to improved auditory performance. Building on these insights, we develop an auditory training app prototype that integrates gamification and narrative design into the auditory training app prototype, and examine their impact on user motivation and engagement. Furthermore, based on the results, we propose design recommendations for future auditory training app development, emphasizing the need to align training effectiveness with user motivation and engagement strategies.

Long video action quality assessment (AQA) aims to evaluate the performance of long-term actions depicted in a video and produce an overall assessment for action quality. A video of long-term actions often contains more complicated temporal and spatial information than that of short-term actions. However, existing approaches that segment a video into individual clips for independent analysis potentially disrupt the narrative flow and diminish contextual details within and across clips, impeding comprehensive video understanding. To address this challenge, we propose an adaptive spatiotemporal graph transformer network (ASGTN) that combines multiple graph structures and transformer attention mechanisms to capture both local and global contextual information within and across clips in a long video. Specifically, the adaptive spatiotemporal graph (ASG) combines a spatial graph branch, designed to enrich the local nuanced spatiotemporal relations within an individual clip, and a temporal graph branch, tailored to dynamically learn the semantic context across different clips. Furthermore, a transformer encoder is integrated to amplify the global dependencies across clips in the entire video. This structure is designed to preserve narrative coherence and maintain essential contextual details in video-level features. Finally, we employ a level-focused decoder to predict the action quality score distribution. Experiments demonstrate that our model achieves state-of-the-art results on popular AQA datasets. Our code is available athttps://github.com/jiangliu5/ASGTN_AQA.

Complementary feeding is crucial to promote healthy nutrition in infant and young children (IYC) and prevent malnutrition. Mothers, families, and healthcare professionals (HCPs) are crucial in helping IYC develop healthy eating habits. However, limited access to adequate nutritional information and health services impacts children’s nutrition, especially in low-resource settings. Technology opens up opportunities to address these challenges and potentially improve IYC feeding practices. Taking a co-design approach, we conducted low-fidelity prototyping workshops with caregivers and HCPs to explore the potential of tangible interfaces to facilitate play and promote healthy nutrition for IYC in two low-resource healthcare settings in Peru. Participants envisioned diverse tangible objects and interactions that could augment the waiting spaces of the healthcare centres, encouraging play and enhancing children’s and caregivers’ experiences, while promoting healthy nutrition and dietary diversity. We outline design opportunities to facilitate tangible play, shared playful experiences, and promote healthy nutrition in low-resource healthcare settings.

Pastoralists in Somaliland are suffering the impacts of climate change, and need relevant, timely, and practical information about water resources and pastures. However, these communities are sparsely distributed and distant from decision-making centres, which impedes rapid dissemination of climate-related information that could allow them to build resilience to climate impacts. Although smartphone adoption rates are low, mobile services are widespread across Somaliland, presenting opportunities for supporting communities through mobile technologies. We interviewed 30 Somali pastoralists to understand their climate information needs, access to technology, and the potential for technology support. We also conducted a focus group with four Somali development experts to explore the cultural context and possible impacts of different design choices. Our results highlight and explore tensions around different design directions, and suggest possible ways to mitigate these. Designing systems that navigate such considerations can contribute to much-needed climate resilience for pastoralist communities in Somaliland and beyond.

Type 1 Diabetes (T1D) self-management requires hundreds of daily decisions. Diabetes technologies that use machine learning have significant potential to simplify this process and provide better decision support, but often rely on cumbersome data logging and cognitively demanding reflection on collected data. We set out to use co-design to identify opportunities for machine learning to support diabetes self-management in everyday settings. However, over nine months of interviews and design workshops with 15 people with T1D, we had to re-assess our assumptions about user needs. Our participants reported confidence in their personal knowledge and rejected machine learning based decision support when coping with routine situations, but highlighted the need for technological support in the context of unfamiliar or unexpected situations (holidays, illness, etc.). However, these are the situations where prior data are often lacking and drawing data-driven conclusions is challenging. Reflecting this challenge, we provide suggestions on how machine learning and other artificial intelligence approaches, e.g., expert systems, could enable decision-making support in both routine and unexpected situations.

Co-design is a widely applied design process with well-documented values, including mutual learning and collective creativity. However, the real-world challenges of conducting multidisciplinary co-design research to inform the design of self-care technologies are not well established. We provide a qualitative account of a multidisciplinary project that aimed to co-design machine learning applications for Type 1 Diabetes (T1D) self-management. Through interviews, we identify not only perceived social, technological and strategic benefits of co-design but also organisational, translational and pragmatic design challenges: participants with T1D experienced difficulties in co-designing systems that met their individual self-care needs as part of group activities; HCI and AI researchers described challenges resulting from applying co-design outcomes to data-driven ML work; and industry collaborators highlighted academic data sharing regulations as cross-organisational challenges that can impede co-design efforts. Based on this understanding, we discuss opportunities for supporting multidisciplinary collaborations and aligning individual health needs with collaborative co-design activities.

The HCI community has a strong and growing interest in shape-changing interfaces (SCIs) that can offer dynamic affordance. In this context, there is an increasing need for HCI researchers and designers to form close relationships with disciplines such as robotics and material science in order to be able to truly harness the state-of-the-art in morphing technologies. To help these synergies arise, we presentMorphino: a card-based toolkit to inspire shape-changing interface designs. Our cards bring together a collection of morphing mechanisms already established in the multidisciplinary literature and illustrate them through familiar examples from nature. We begin by detailing the design of the cards, based on a review of shape-change in nature; then, report on a series of design sessions conducted to demonstrate their usefulness in generating new ideas and in helping end-users gain a better understanding of the possibilities for shape-changing materials.

Traditional approaches to psychotherapy emphasise face-to-face contact between patients and therapists. In contrast, current computerised approaches tend to minimise this contact. This can limit the range of mental health difficulties for which computerised approaches are effective. Here, we explore an alternative approach that integrates face-to-face contact, electronic contact, online collaboration, and support for between-session activities. Our discussion is grounded in the design of a platform to deliver psychotherapy for depression. We report findings of an 11-month pragmatic study in which 17 patients received treatment for depression via the platform. Results show how design decisions had a significant impact on the dynamics of therapeutic sessions and the establishment of patient-therapist relationships. For example, the use of instant messaging for synchronous, in-session contact slowed communication, but also provided a valuable space for reflection and helped to maintain session focus. We discuss the impact of flexibility and the potential of integrated approaches to both enhance and reduce patient engagement.

Habit formation is an important part of behavior change interventions: to ensure an intervention has long-term effects, the new behavior has to turn into a habit and become automatic. Smartphone apps could help with this process by supporting habit formation. To better understand how, we conducted a 4-week study exploring the influence of different types of cues and positive reinforcement on habit formation and reviewed the functionality of 115 habit formation apps. We discovered that relying on reminders supported repetition but hindered habit development, while the use of event-based cues led to increased automaticity; positive reinforcement was ineffective. The functionality review revealed that existing apps focus on self-tracking and reminders, and do not support event-based cues. We argue that apps, and technology-based interventions in general, have the potential to provide real habit support, and present design guidelines for interventions that could support habit formation through contextual cues and implementation intentions.

Despite the fact that a third of all cases of unintentional medication non-adherence are caused by simple forgetfulness, the majority of interventions neglect this issue. Even though patients have access to smartphone applications ("apps") designed to help them remember medication, neither their quality nor effectiveness has been evaluated yet. We report the findings of a functionality review of 229 medication reminder apps and a thematic analysis of their 1,012 user reviews. Our research highlights the gap between the theory and practice: while the literature shows that many medication regimens are habitual in nature and the presence of daily routines supports remembering, existing apps rely on timer-based reminders. To address this disparity, we present design requirements for building medication reminders that support the routine aspect of medication-taking and its individual nature, and demonstrate how they could be implemented to move from passive alerts to a smarter memory and routine assistant.