Playing cards have long been a central feature in board games, despite their physical limitations, such as fragility, and repetitive content. Yet, while HCI research increasingly explores augmented board games, interactive playing cards remain underexplored. In this work, we investigate the use of e-paper displays as interactive playing cards. Based on a formative study with eight game designers, we designed and implemented InkStack—a prototype consisting of e-paper cards, a dedicated programmer, and a web application for card customisation. We then evaluated InkStack in a within-subject study with n = 20 participants, comparing its use across four board game mechanics against traditional paper cards and a smartphone. Results show that InkStack is preferred for more complex mechanics, whereas paper and smartphones are sufficient for simpler tasks. The findings also highlight how customisation and versatility can enhance gameplay and enable novel forms of interaction.

While technology is widely recognised as a tool to enhance wellbeing, there is no clear consensus on the best practices for design. Persuasive strategies, such as nudging, are often seen as effective but raise ethical concerns. Reflection-based approaches offer a potential alternative. However, a clear understanding of the balance between these strategies is crucial for designing effective and ethically sound wellbeing technologies. We conducted two studies with a total of n = 163 participants comparing nudging and reflection techniques using contrasting prototypes of fitness wearables. We verified that the prototypes represented key nudging and reflection strategies through expert feedback. Our mixed-methods inquiry shows that certain nudging strategies are perceived as more malicious and more likely to provoke rumination, i.e., negative thought cycles, compared to other wellbeing strategies. We contribute insights to inform design decisions for wellbeing technologies, balancing effectiveness with ethical considerations.

Figure 1: Motion capture tags, accelerometer sensors layout and game setup.

The integration of motion capture technology into dance education is gaining traction, offering new possibilities for enhancing precision and technique. Traditional methods, such as instructor feedback and mirror observation, often lack the granularity required for effective self-correction, particularly among beginners. In this study, we evaluate the OptiTrack motion capture system for teaching basic dance movements, comparing it with traditional instructor feedback in a between-subjects study involving 28 novice dancers. The system proved more precise in detecting subtle posture misalignments—especially during dynamic movements such as pirouettes—yet participants expressed a clear preference for the real-time, personalised guidance. Our findings suggest that dance learning support systems could be strengthened by complementing technical accuracy with qualities such as interpersonal aspects and motivational feedback.

Despite the wide adoption of wearables, electronics incorporated into jewellery remain a niche. Interactive jewellery offers a compelling design space, encompassing values of traditional jewellery and its socio-cultural roles. However, creating interactive artefacts that bear symbolic and social meaning remains challenging. We investigate how these roles can be leveraged and re-interpreted using modern technology. Utilising traditional jewellery’s socio-cultural roles as a framework, we look at interactive jewellery in participatory workshops with N = 16 design practitioners. Informed by our results, we created a prototype interactive necklace, focusing on Identity role and conducted four case studies to probe the wearer and bystander perceptions on interactive jewellery in different social contexts. Based on our findings, we contribute four directions for interactive jewellery designers.

Traditional methods for teaching electromagnetism often fall short, constrained by complex math and static 2D diagrams that fail to convey the dynamic, 3D nature of Electromagnetic fields. Even modern interactive tools frequently offer only scripted experiences, limiting exploration. This work presents a novel VR application designed to overcome these challenges by providing an interactive, real-time simulation of fundamental electromagnetic phenomena.

Smart homes are evolving into complex ecosystems, but their inner workings often remain opaque to users, limiting their ability to troubleshoot and customise the technology. The distributed and hidden components make it challenging for users to understand how these systems work. To design interfaces that enable intuitive troubleshooting for non-experts, we first need a clear understanding of how they form mental models and instinctively diagnose issues. We conducted three iterative vignette studies with realistic smart home scenarios to explore how users perceive interconnectivity in smart home ecosystems and how system complexity impacts their troubleshooting approaches. We identified common smart home topologies envisioned by users and categorised their diagnostic strategies. Our findings show that while users view their smart homes as hierarchical, their mental models are often incomplete, and current interfaces favour functional models, hiding the connections in the system. We provide seven actionable takeaways for designing interfaces that improve user understanding and troubleshooting capabilities.

Building tangible interfaces or data physicalizations is a resource-intensive endeavour. There is a need for rapid means to prototype tangibles in order to facilitate research and design. To this end, we designed ProtoBricks: a research toolkit that uses capacitive bricks to facilitate rapid prototyping for tangible interfaces. Utilizing toy bricks that do not contain electronics, ProtoBricks can record brick position and color. Specialized knowledge is not required to build our system as it uses widely available components and 3D printing. We contribute the full software and hardware specification of the toolkit. We evaluate the utility of the toolkit by reporting on past use cases and prototyping workshops. We show that the toolkit facilitates creativity and effectively supports prototyping. ProtoBricks lowers the entry threshold for experimenting with tangible interfaces and enables researchers and designers to focus on the interaction with their prototype, delegating implementation to the toolkit.

Abstract Remote health monitoring (RHM) provides various benefits to older adults, but its use is still limited. Remote monitoring may help in avoiding emergencies and prolong users’ independence. To understand how to design systems which support older adults, we studied a large-scale remote health monitoring system. The system used fitness-grade smartwatches to monitor the vital signs of more than 2000 users constantly. To probe the lived experience of using RHM, we conducted an explorative interview study (N = 41) with operators, carers, and users of the RHM system. Our thematic analysis reveals that personalisation of care ecology is crucial for developing users’ confidence and trust in the system. We found that participation in RHM may catalyse positive changes in older adults’ lifestyles. Based on our findings, we formulate five recommendations for designing future health monitoring systems. Our work contributes to insights into the lived experience and stakeholder ecology of health monitoring systems.

A rapid shift towards online education witnessed in recent years, re-shaped the necessary skill set of a modern teacher. Delivery of classes in remote and hybrid format became an integral part of education. However, providing feedback on lecturing technique at scale still remains a challenge. We present the design and implementation of Speecoach – an online tool for lecturers that analyses the audio recordings of lectures and provides feedback concerning their style of speech delivery. Our system analyses the pitch, speech rate and volume dynamics of a recording and compares it against the reference model based on a data set of professional-grade talks. Our tool facilitates teachers’ self-development by providing contextualised feedback on the parameters of their speech and comparing it to different forms of public addresses. Our work contributes a prototype tool facilitating public speaking and envisions future developments and studies in life-long learning of education professionals.

Human perception lacks the capabilities to accurately assess distance. The recent Covid-19 pandemic outbreak rendered this ability particularly important. Augmenting our sense of distance can help maintain safe separation from others when required. To explore how systems can help users maintain physical distance, we designed, implemented and evaluated Gapeau—a head-mounted system for augmenting the sense of distance. Our system uses proximity sensors and thermal sensing to detect and measure the distance to other people. We conducted a validation protocol, an experiment, in which we compared different feedback modalities, and an in-the-wild study to evaluate Gapeau’s performance and suitability for use in social contexts. We found that our system enabled users to more accurately determine whether they were maintaining a safe distance from others. Vibration and auditory feedback were found most effective and usable. Gapeau was perceived as socially acceptable. Our work contributes insights for augmented sensing systems with social relevance.

Due to multimodal approach, the virtual reality experiences become increasingly more immersive and entertaining. New control modalities, such as brain-computer interfaces (BCIs), enable the players to engage in the game with both their bodies and minds. In our work, we investigate the influence of employing BCI-driven mechanics on player’s in-game immersion. We designed and implemented an escape room-themed game which employed player’s mental states of focus and relaxation as input for selected game mechanisms. Through a between-subject user study, we found that controlling the game with mental states enhances the in-game immersion and attracts the player’s engagement. At the same time, using BCIs did not impose additional cognitive workload. Our work contributes qualitative insights on psychocognitive effects of using BCIs in gaming and describing immersive gaming experiences.

Although robots have become an everyday companion for medical personnel in various domains, few solutions have been crafted to facilitate therapy of psychological disorders. Treatment of phobias is one of the areas which could highly benefit from introducing device-mediated interactions. To address the challenges of arachnophobia therapy, we designed SpiderHand - robot-based system for quasi-direct interaction with unpleasant creatures. We first identified the challenges of cognitive-behavioral therapy through interviews with a professional therapist and elicited functional requirements through experimental inquiry. Then, we designed and implemented an operational research prototype of motion-controlled robotic manipulator including remote touch features. We contribute a complete implementation toolkit for constructing DIY robot manipulator and provide insights on designing interactive robots for psychological therapy.

While the sport of golf offers unique opportunities for people of all ages to be active, it also requires mastering complex movements before it can be fully enjoyed. Extensive training is required to begin achieving any success, which may demotivate prospective players away from the sport. To aid beginner golfers and enable them to practice without supervision, we designed Subtletee---a system that enhances the bodily awareness of golfers by providing feedback on the position of their feet and elbows. We first identified key problems golf beginners face through expert interviews. We then evaluated different feedback modalities for Subtletee---visual, tactile and auditory in an experiment with 20 beginner golfers. We found that providing proprioception feedback increased the users' performance on the driving range, with tactile feedback providing the most benefits. Our work provides insights on delivering feedback during physical activity that requires high precision movements.

This paper investigates the potential of using an electromyographic gesture recognition armband as an everyday companion for operating mobile devices in awareness-requiring contexts and suggests the fields, in which further developments are advisable.The Myo armband from Thalmic Labs is a fully functional motion controller, based on gesture recognition through EMG muscle sensing.The device has been applied for audio control, and the usability and relevance of the gestural interaction have been examined.Participants were asked to operate on a recording while cycling, and a reference group performed similar task in leisure context.The gathered answers suggest decent potential of gestural interaction manner for environments requiring high visual attention, eg.driving or cycling.However, the current state of the solution acts in too sensitive way, as processing numerous misinterpreted gestures highly decreases the system's usability.Moreover, gestures employed are perceived as too apparent and intrusive for social interactions.

The subject of this paper is to compare two different modality multi-touch interactive surfaces based on both: user experience and results of measurements in order to examine how different properties influence usefulness, in specific, their fitness to act as a "coffee table".Tests were conducted on the Microsoft PixelSense (AKA Surface) and a Samsung touch screen overlay both 40+ inches diagonally.The study covers analysis of obtained measurements and summary of user experience collected over a number of summits and experiments.While tests for both devices returned very similar results, with the overlay more favorable, neither device could truly fit the tested use case due to their inconvenience, form factor and other issues.

The paper describes application of the crowdsourcing system to pre-process X-ray tomography images.In this paper, we show the analysis of the crowdsourcing system applied to process tomography imaging to investigate granular flow with aid of tracking particles.Applying crowdsourcing approach coupled with a proper system interface design enhances the performance of the workers and elevates the attitude.We show here how analysis of the proposed systems in terms of user adoption and performance.Proposed interface features are designed based on previous work evaluation in order to reduce the cognitive and physical workload demands.

In this article, we present a novel application domain for human computation, specifically for crowdsourcing, which can help in understanding particle-tracking problems. Through an interdisciplinary inquiry, we built a crowdsourcing system designed to detect tracer particles in industrial tomographic images, and applied it to the problem of bulk solid flow in silos. As images from silo-sensing systems cannot be adequately analyzed using the currently available computational methods, human intelligence is required. However, limited availability of experts, as well as their high cost, motivates employing additional nonexperts. We report on the results of a study that assesses the task completion time and accuracy of employing nonexpert workers to process large datasets of images in order to generate data for bulk flow research. We prove the feasibility of this approach by comparing results from a user study with data generated from a computational algorithm. The study shows that the crowd is more scalable and more economical than an automatic solution. The system can help analyze and understand the physics of flow phenomena to better inform the future design of silos, and is generalized enough to be applicable to other domains.

A new method to solve the inverse problem of electrical capacitance tomography is proposed. Our method is based on artificial neural network to estimate the radius of an object present inside a pipeline. This information is useful to predict the distribution of material inside the pipe. The capacitance data used to train and test the neural network is simulated on Matlab using the electrical capacitance tomography toolkit ECTsim. The provided accuracy is promising and shows efficiency to solve the inverse problem in a simple manner and on reduced computational time about 120 times when compared to the existing Landweber iterative algorithm for tomographic image reconstruction that can be encouraging for dynamic industrial applications.

This paper describes the design of a system providing room occupancy information in a university campus. The system and its possible influence on the human environment are designed to enhance the work environment through pervasive information delivery. The work is motivated by recent advances in the domain of ubiquitous computing. The authors describe a case study of delivering a solution to university students informing them where they can find free spaces in rooms designated for quiet study. The data is available on the web and through ambient displays. The proof-of-concept study presents the methodology applied, discusses the design issues that were encountered by the project team and reflects on the devices and techniques used in the implementation. An application of standard image processing techniques to provide a contextualized, pervasive user-centered service is also depicted.

This papers shows attempt of using prior knowledge in order to learn about the industrial process system behaviour. The system being studied here is the pneumatic conveying of solids monitored with electrical capacitance tomography (ECT). The prior knowledge is the non-invasive measurement information derived on the basis of intentionally introduced structural change in the experimental process flow rig. The focus is on the examination of pseudo-emergency states of bulk flow. Real case pneumatic transport failure usually consists in pipeline blockage. Such blockage typically develops starting as material slug build up. In contrast, our experiments investigate artificially induced flow pre-blockage states monitored with ECT measurement system. Collected measurement data are contextually processed in order to detect the pipeline state in sense of flow regime and flow behaviour. ECT raw data analysis strives to uncover a relation between measured values and flow change tendency. This research is aimed at giving rise to conclusions about possibility of contextual data processing in order to properly adjust pneumatic conveying control and a possible role of ECT records in this aspect. Authors show here that for now it is possible to detect abnormal process state such as blockage signal and the presented methodology coupled with nowadays computational techniques are anticipated to lead to abnormal states forecasting such as blockage threat recognition.

Advanced statistical modelling such as Bayesian framework is a powerful methodology and gives great flexibility in terms of physical phenomena modelling. Unfortunately it is usually associated with very time and resource consuming computing. Therefore it was avoided by engineers in the past. Nowadays, rapid development of computer capabilities enables use of such methods. Algorithms reported here are based on Markov chain Monte Carlo (MCMC) methods applied to Bayesian modelling. The important factor is highly iterative approach enabling direct desired parameters estimation, hence omitting the phase of image reconstruction. This property has an important feature of making feasible implementation of automatic industrial process control systems based on process tomography.

The development of the mass flow rate measurements in the industrial systems using a twin-planes electrical capacitance tomography (ECT) system is presented. The mass flow measurement is based on cross-section decomposition into homogenous regions and virtual channel is then defined as connecting of two homogenous regions of different sensor planes. The decomposition has been obtained by using a stochastic flow model. As a result the set of virtual channels is obtained instead the complex flow inside a single physical channel. The authors present the results of investigation for turbulent flow propagation using the virtual channel concept also.