InSense3D: Designing Smart 3D-Printed Structures Leveraging Ferromagnetic Filaments for Inductive Deformation SensingIn this paper, we explore the design and development of passive soft 3D-printed structures whose deformation can be sensed accurately without any wired connection. By 3D printing tangible interfaces consisting of flexible TPU (thermoplastic polyurethane), made from lattice structures with bespoke geometries and mechanical properties, and ferromagnetic elements using metal-infused filaments, we enable the detection of structural deformations through inductive sensing. We investigate how different ferromagnetic core configurations within flexible substrates, guided by key design parameters, influence the sensitivity, responsiveness, and deformability of the sensing system. We demonstrate that our 3D-printed inductive sensing approach allows users to switch their fully passive tangible interfaces for specialized tasks without assembly or the need to unplug wires. Our sensing approach can be integrated in portable applications, such as a smart bottle cover that captures subtle deformation to measure liquid intake, or in wearable applications, such as monitoring foot pressure in smart shoes.2026RBRahul Bhaumik et al.Free Universitv of Bozen-BolzanoShape-Changing Interfaces & Soft Robotic MaterialsBiosensors & Physiological MonitoringCircuit Making & Hardware PrototypingCHI
Are Semantic Networks Associated with Idea Originality in Artificial Creativity? A Comparison with Human AgentsThe application of generative artificial intelligence in Creativity Support Tools (CSTs) presents the challenge of interfacing two black boxes: the user's mind and the machine engine. According to Artificial Cognition, this challenge involves theories, methods, and constructs developed to study human creativity. Consistently, the paper investigated the relationship between semantic networks organisation and idea originality in Large Language Models. Data was collected by administering a set of standardised tests to ChatGPT-4o and 81 psychology students, divided into higher and lower creative individuals. The expected relationship was confirmed in the comparison between ChatGPT-4o and higher creative humans. However, despite having a more rigid network, ChatGPT-4o emerged as more original than lower creative humans. We attributed this difference to human motivational processes and model hyperparameters, advancing a research agenda for the study of artificial creativity. In conclusion, we illustrate the potential of this construct for designing and evaluating CSTs.2026UDUmberto Domanti et al.Free University of Bozen-BolzanoGenerative AI (Text, Image, Music, Video)Human-LLM CollaborationCreative Collaboration & Feedback SystemsCHI
Knitted Inductive Flex Sensors for Wearable ApplicationsWe introduce a knitted inductive flex sensor which seamlessly integrates a coil and a capacitor into a soft and flexible tubular knit. By knitting enameled copper wires, we form a self-supporting coil, whose inductance changes with stretching and bending. Knitting both a coil and a parallel-wire capacitor, we create a textile resonant LC circuit, while preserving the softness, elasticity, and breathability of knitted textiles. In this paper, we present the fabrication process using an industrial knitting machine, evaluate sensor sensitivity and hysteresis over 100 bending cycles, and demonstrate the sensors versatility across joints of different radii. Our results show that knitted inductive sensors combine the wearability of soft textiles with the stability of inductive sensing, opening new sensing opportunities in healthcare, rehabilitation, and interactive electronic garments.2026MHMira A. Haberfellner et al.Free University of Bolzano-BozenHaptic WearablesElectronic Textiles (E-textiles)Biosensors & Physiological MonitoringCHI
Embroidering Resonant Circuits for Inductive Pressure SensingIn this paper, we introduce an embroidered resonant circuit for textile-based inductive pressure sensing. By embroidering enameled wire onto a flexible textile, we create a coil and a capacitor using a single continuous wire. This resonant circuit, combined with a ferromagnetic layer and a soft, compressible material such as foam, forms the basis of a flexible and soft pressure sensor. We investigate the fabrication of coils and capacitors through embroidery, evaluate different conductive materials for altering the circuit's resonance frequency, and assess the impact of different foams on the sensor's performance. Following our tests, we evaluated an embroidered sensor with a diameter of 45 mm, actuated with a force of up to 50 N over 100 cycles, using foams with different compression strengths. A series of applications demonstrate that our approach offers a performant complement to existing sensing methods used in electronic textiles.2025APAndreas Pointner et al.Electronic Textiles (E-textiles)Circuit Making & Hardware PrototypingUIST
Exposing the Ideology of Large Language Models with Creative PracticesIdeology is power exerted by language, whether generated by humans or machines. It manifests in the biases produced by Large Language Models (LLMs), reflecting power relations between users and providers. Following this assumption, we engaged in an artistic critique of how ChatGPT produces ideology. We conducted two experiential workshops with 20 artists, analysing their reflections and interactions through ethnographic inquiry and formal linguistic analysis grounded in Thompson’s account of ideology. The artists reported that both commercial goals and debiasing efforts constrain artistic expression, reinforcing dominant cultural values. To support critical engagement, we introduce a framework that maps recurring linguistic patterns in ChatGPT outputs to ideological modes of operation. This framework offers HCI practitioners an analytical tool to interrogate the socio-political implications of LLMs in design contexts. Our findings highlight the role of artists as critical agents in socio-technical transitions and call for interdisciplinary approaches to language technology critique.2025MCMichele Cremaschi et al.Human-LLM CollaborationAI Ethics, Fairness & AccountabilityTechnology Ethics & Critical HCIDIS
SqueezeMe: Creating Soft Inductive Pressure Sensors with Ferromagnetic ElastomersWe introduce SqueezeMe, a soft and flexible inductive pressure sensor with high sensitivity made from ferromagnetic elastomers for wearable and embedded applications. Constructed with silicone polymers and ferromagnetic particles, this biocompatible sensor responds to pressure and deformation by varying inductance through ferromagnetic particle density changes, enabling precise measurements. We detail the fabrication process and demonstrate how silicones with varying Shore hardness and different ferromagnetic fillers affect the sensor's sensitivity. Applications like weight, air pressure, and pulse measurements showcase the sensor’s versatility for integration into soft robotics and flexible electronics.2025TPThomas Preindl et al.Free University of Bozen-Bolzano, Faculty of EngineeringHaptic WearablesShape-Changing Interfaces & Soft Robotic MaterialsCHI
Interaction with a 3D Surface for an Innovative Input Experience on a Central ConsoleThis paper explores the development of a touch-sensitive interactive 3D central console for vehicles aimed at simplifying access to tasks unrelated to driving, such as adjusting seats and controlling music. We investigated three console designs with front surface angles of 45°, 90° and 135°. The initial study assessed how users interact with these three prototypes. Subsequently, we examined the ease with which users could reach across the different shapes. Additionally, we conducted a gesture elicitation study styled on guessability with the 135° model, focusing on user interaction with four applications: a radial menu, a 2D menu, car seat adjustments, and map navigation. Summarizing, this work aims to create a central console that is ergonomic, minimalist, and utilizes surface gestures, setting a new standard for future car interiors.2024RBRahul Bhaumik et al.Head-Up Display (HUD) & Advanced Driver Assistance Systems (ADAS)In-Vehicle Haptic, Audio & Multimodal FeedbackAutoUI
A Steampunk Critique of Machine Learning AccelerationThe application of Machine Learning is driven by the techno-capitalist struggle for productivity across various domains, including the creative industry. Sociological research has demonstrated how technology-induced temporality introduces challenges at the individual and societal levels. Art creativity conflicts with speed and mass production. This paper describes Isotta, a critical artefact combining a Mignon typewriter and a Language Model to spark discussion about ML-induced acceleration. Fourteen artists evaluated Isotta in an interview study, and semiotics was used as the analytical lens. Results exposed ideological assumptions around the consequences of technology in the writing realm. We discuss these insights in the context of interactive design in times of techno-capitalistic acceleration. Our findings highlight the significance of temporal factors in designing generative writing interactions and underscore how complex societal challenges can be approached in design through the contrast-eliciting property that outdated technologies offer when juxtaposed with contemporary technologies.2024MCMichele Cremaschi et al.Technology Ethics & Critical HCIDesign FictionDIS
Threads of Traceability: Textile IDs in the Fabric of Sustainable FashionTextile fabrication, an ancient human technology, has evolved over millennia, transitioning from a focus on affordability and speed to a current emphasis on sustainability. With Textile ID, we envision a digital garment passport that seamlessly incorporates directly into textile surfaces as a design element to bridge the gap between sustainability and consumer engagement, transforming garments into interactive storytellers of their ecological journey. The visual surface of the garment can be scanned with a smartphone to access a unique identifier embedded within the fabric, which provides essential information about the product's lifecycle. This work discusses the design space of various visual and textile parameters, proposes design possibilities and insights for implementation. Finally, we showcase a set of sample garment designs and provide design recommendations for designers to use in their future work.2024MHMira Alida Haberfellner et al.Customizable & Personalized ObjectsEcological Design & Green ComputingDIS
Querying the Quantification of the Queer: Data-Driven Visualisations of the Gender SpectrumCritical data studies denounce that heteronormative formalisations of sex/gender identity obscure queer lives from datasets and computational processes. Since sex/gender categories cannot convey nonbinarity and multiplicity, this project addresses the inherent tension between queerness and systematisation with an anticategorical quantitative visual approach, combining psychometric scales with visualisations of the gender spectrum. Indeed, using queer and feminist methodologies, we propose a new data structure resulting from the codesign of an interactive visualisation of the gender spectrum, made in an iterative dialogue with gender-diverse people. Our contribution is twofold: an inclusive data structure for the self-assessment of sex/gender identity, and an interactive visualisation, acting as a critical design object, educational and counselling tool, and basis for data collection, annotation, and analysis. Although aware that this project could both empower and harm sexual minorities, its originality is seeing nonbinarity and multiplicity not as appendices to a normative system, but as queering design principles2024FSFe Simeoni et al.Universal & Inclusive DesignGender & Race Issues in HCIEmpowerment of Marginalized GroupsDIS
Loopsense: low-scale, unobtrusive, and minimally invasive knitted force sensors for multi-modal input, enabled by selective loop-meshingIntegrating sensors into knitted input devices traditionally comes with considerable constraints for textile and UI design freedom. In this work, we demonstrate a novel, minimally invasive method for fabricating knitted sensors that overcomes this limitation. We integrate copper wire with piezoresistive enamel directly into the fabric using weft knitting to establish strain and pressure sensing cells that consist only of single pairs of intermeshed loops. The result is unobtrusive and potentially invisible, which provides tremendous latitude for visual and haptic design. Furthermore, we present several variations of stitch compositions, resulting in loop meshes that feature distinct response with respect to direction of exerting force. Utilizing this property, we are able to infer actuation modalities and considerably expand the device's input space. In particular, we discern strain directions and surface pressure. Moreover, we provide an in-depth description of our fabrication method, and demonstrate our solution's versatility on three exemplary use cases.2024RARoland Aigner et al.University of Applied Sciences Upper AustriaShape-Changing Interfaces & Soft Robotic MaterialsOn-Skin Display & On-Skin InputCircuit Making & Hardware PrototypingCHI
spaceR: Knitting Ready-Made, Tactile, and Highly Responsive Spacer-Fabric Force Sensors for Continuous InputWith spaceR, we present both design and implementation of a resistive force-sensor based on a spacer fabric knit. Due to its softness and elasticity, our sensor provides an appealing haptic experience. It enables continuous input with high precision due to its innate haptic feedback and can be manufactured ready-made on a regular two-bed weft knitting machine, without requiring further post-processing steps. For our multi-component knit, we add resistive yarn to the filler material, in order to achieve a highly sensitive and responsive pressure sensing textile. Sensor resistance drops by ~90% when actuated with moderate finger pressure of 2 N, making the sensor accessible also for straightforward readout electronics. We discuss related manufacturing parameters and their effect on shape and electrical characteristics and explore design opportunities to harness visual and tactile affordances. Finally, we demonstrate several application scenarios by implementing diverse spaceR variations, including analog rocker- and four-way directional buttons, and show the possibility of mode-switching by tracking temporal data.2022RARoland Aigner et al.Haptic WearablesShape-Changing Interfaces & Soft Robotic MaterialsUIST
Decision Making Strategies Differ in the Presence of Collaborative Explanations: Two Conjoint StudiesRating-based summary statistics are ubiquitous in e-commerce, and often are crucial components in personalized recommendation mechanisms. Especially visual rating summarizations have been identified as important means to explain, why an item is presented or proposed to an user. Largely left unexplored, however, is the issue to what extent the descriptives of these rating summary statistics influence decision making of the online consumer. Therefore, we conducted a series of two conjoint experiments to explore how different summarizations of rating distributions (i.e., in the form of number of ratings, mean, variance, skewness, bimodality, or origin of the ratings) impact users' decision making. In a first study with over 200 participants, we identified that users are primarily guided by the mean and the number of ratings, and -- to lesser degree -- by the variance and origin of a rating. When probing the maximizing behavioral tendencies of our participants, other sensitivities regarding the summary of rating distributions became apparent. We thus instrumented a follow-up eye-tracking study to explore in more detail, how the choices of participants vary in terms of their decision making strategies. This second round with over 40 additional participants supported our hypothesis that users, who usually experience higher decision difficulty, follow compensatory decision strategies, and focus more on the decisions they make. We conclude by outlining how the results of these studies can guide algorithm development, and counterbalance presumable biases in implicit user feedback.2019LCLudovik Coba et al.Eye Tracking & Gaze InteractionExplainable AI (XAI)Recommender System UXIUI
Prediction of Music Pairwise Preferences from Facial ExpressionsUsers of a recommender system may be requested to express their preferences about items either with evaluations of items (e.g. a rating) or with comparisons of item pairs. In this work we focus on the acquisition of pairwise preferences in the music domain. Asking the user to explicitly compare music, i.e., which, among two listened tracks, is preferred, requires some user effort. We have therefore developed a novel approach for automatically extracting these preferences from the analysis of the facial expressions of the users while listening to the compared tracks. We have trained a predictor that infers user's pairwise preferences by using features extracted from these data. We show that the predictor performs better than a commonly used baseline, which leverages the user's listening duration of the tracks to infer pairwise preferences. Furthermore, we show that there are differences in the accuracy of the proposed method between users with different personalities and we have therefore adapted the trained model accordingly. Our work shows that by introducing a low user effort preference elicitation approach, which, however, requires to access information that may raise potential privacy issues (face expression), one can obtain good prediction accuracy of pairwise music preferences.2019MTMarko Tkalcic et al.Human Pose & Activity RecognitionRecommender System UXIUI
Guideline-Based Evaluation of Web ReadabilityEffortless reading remains an issue for many Web users, despite a large number of readability guidelines available to designers. This paper presents a study of manual and automatic use of 39 readability guidelines in webpage evaluation. The study collected the ground-truth readability for a set of 50 webpages using eye-tracking with average and dyslexic readers (n = 79). It then matched the ground truth against human-based (n = 35) and automatic evaluations. The results validated 22 guidelines as being connected to readability. The comparison between human-based and automatic results also revealed a complex framework: algorithms were better or as good as human experts at evaluating webpages on specific guidelines – particularly those about low-level features of webpage legibility and text formatting. However, multiple guidelines still required a human judgment related to understanding and interpreting webpage content. These results contribute a guideline categorization laying the ground for future design evaluation methods.2019AMAliaksei Miniukovich et al.University of TrentoExplainable AI (XAI)Recommender System UXCognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)CHI