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The addition of haptic feedback in digital musical instruments (DMIs) can improve performance control and expressivity. The TorqueTuner is a family of embedded rotary force-feedback modules that enable DMI designers to map haptic effects to musical parameters, facilitating straightforward haptic integration. In this demonstration, we present 3 TorqueTuner iterations based on different motors and drivers: 1) the newly redesigned Mechaduino (forked from an obsolete open-source servo platform by Tropical Labs), 2) the Mjbots Moteus (a high-power industrial motor), and the Makerfabs MaTouch SmartKnob (a self-contained device with a display). Attendees will interact with and compare each iteration, experiencing rotary haptic effects applied to a live musical context. Ultimately, we aim for this demonstration to lead to greater and easier integration of haptics into DMIs

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Creative coding is the use of programming as a medium for creative expression, often to produce interactive, generative, or audiovisual works. This 1.5-hour special session will bring together panelists with experience teaching creative coding courses at the university or equivalent level. The format will include approximately 60 minutes of lightning talks by 4–6 panelists from multidisciplinary backgrounds, including art, computer science, and engineering, followed by a combined discussion and networking segment to foster exchange among all participants

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Haptics has been a NIME topic right from the start: word stem “haptic“ was mentioned in NIME’01 workshop papers, and then part of a publication title for the first time at NIME’02, the first NIME conference], while NIME keynote presenters focused or discussed HMA on several occasions (e.g. 2003, 2013, 2015 & 2019). There are 49 occurrences of the word “haptic” in titles and 84 in abstracts for NIME paper proceedings up to 2025, as searchable in the github repository versioning the NIME bibliography.
Though common in NIME, Haptic Musical Artifacts (HMA) can only be experienced in person. With the exception of a few sub-categories of haptic hardware that are widely deployed, for instance, vibrotactile haptics in mobile phones, most HMA remain confined to research labs. Force-Feedback devices, on the other hand, are much less available to the NIME community. They tend to be expensive and demand hardware and software specifications which are not straightforward to implement. Furthermore, these devices become rapidly obsolete as computer hardware and software evolve, making them even less accessible. Finally, the replicability of such devices is not evident due to proprietary protocols (firmware, drivers, etc.) and the unavailability of original electronic circuits. All these issues have a decisive negative impact on the sustainability of haptic research in NIME and elsewhere, with most projects having a lifespan of a few years (typically the duration of a PhD thesis).
This workshop aims to present a retrospective review of HMA, specifically, force-feedback devices used in musical applications, accompanied by hands-on demonstrations, to provide NIME attendees with an opportunity to revisit and experience research on haptics and music. Furthermore, a general discussion will be held on ways to create a consortium of researchers interested in the replicability and sustainability of HMA within the NIME community.

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As Artificial Intelligence (AI) conversational agents become widespread, people are increasingly using them for health information seeking. The use of off-the-shelf conversational agents for health information seeking could place high metacognitive demands (the need for extensive monitoring and control of one's own thought process) on individuals, which could compromise their experience of seeking health information. However, currently, the specific demands that arise while using conversational agents for health information seeking, and the strategies people use to cope with those demands, remain unknown. To address these gaps, we conducted a think-aloud study with 15 participants as they sought health information using our off-the-shelf AI conversational agent. We identified the metacognitive demands such systems impose, the strategies people adopt in response, and propose considerations for designing beyond off-the-shelf interfaces to reduce these demands and support better user experiences and affordances in health information seeking.

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Extended Reality (XR) has advanced audiovisual immersion, yet haptic feedback, especially for the lower body, remains limited. We present RoboHaptics, the first system to explore lower-body haptics using commercial quadruped robots. RoboHaptics leverages its freestanding and reconfigurable nature to deliver both active and passive tactile feedback without requiring worn devices. We contribute a design space for quadruped-mediated haptics, a software toolkit with a programmable library of tactile effects, and empirical evaluations showing that quadruped robots can deliver safe force feedback from 3–28 N (below nociceptive thresholds), reach lower-body locations with precision of 2.1–5.1 mm and accuracy of 3.7–17 mm, and support a wide range of tactile effects. A 12-participant study further revealed significant inputs into how RoboHaptics can be used to increase realism and immersion by providing lower-body haptic feedback. Together, our work establishes quadruped robots as a versatile platform for mobile, off-body haptics in XR.

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We introduce MapStory, an LLM‑powered animation prototyping tool that generates editable map animation sequences directly from natural language text by leveraging a dual-agent LLM architecture. Given a user-written script, MapStory automatically produces a scene breakdown, which decomposes the text into key map animation primitives such as camera movements, visual highlights, and animated elements. Our system includes a researcher agent that accurately queries geospatial information by leveraging an LLM with web search, enabling automatic extraction of relevant regions, paths, and coordinates while allowing users to edit and query for changes or additional information to refine the results. Additionally, users can fine-tune parameters of these primitive blocks through an interactive timeline editor. We detail the system’s design and architecture, informed by formative interviews with professional animators and by an analysis of 200 existing map animation videos. Our evaluation, which includes expert interviews (N=5), and a usability study (N=12), demonstrates that MapStory enables users to create map animations with ease, facilitates faster iteration, encourages creative exploration, and lowers barriers to creating map-centric stories.

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We introduce a novel component for smart garments: smart interlining, and validate its technical feasibility through a series of experiments. Our work involved the implementation of a prototype that employs a textile vibration sensor based on Triboelectric Nanogenerators (TENGs), commonly used for activity detection. We explore several unique features of smart interlining, including how sensor signals and patterns are influenced by factors such as the size and shape of the interlining sensor, the location of the vibration source within the sensor area, and various propagation media, such as airborne and surface vibrations. We present our study results and discuss how these findings support the feasibility of smart interlining. Additionally, we demonstrate that smart interlinings on a shirt can detect a variety of user activities involving the hand, mouth, and upper body, achieving an accuracy rate of 93.9% in the tested activities.

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In this work, we introduce a formal design approach derived from the performing arts to design robot group behaviour. In our first experiment, we worked with professional actors, directors, and non-specialists using a participatory design approach to identify common group behaviour patterns. In a follow-up studio work, we identified twelve common group movement patterns, transposed them into a performance script, built a scale model to support the performance process, and evaluated the patterns with a senior actor under studio conditions. We evaluated our refined models with 20 volunteers in a user study in the third experiment. Results from our affective circumplex modelling suggest that the patterns elicit positive emotional responses from the users. Also, participants performed better than chance in identifying the motion patterns without prior training. Based on our results, we propose design guidelines for social robots’ behaviour and movement design to improve their overall comprehensibility in interaction.

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We are increasingly adopting domestic robots (e.g., Roomba) that provide relief from mundane household tasks. However, these robots usually only spend little time executing their specific task and remain idle for long periods. They typically possess advanced mobility and sensing capabilities, and therefore have significant potential applications beyond their designed use. Our work explores this untapped potential of domestic robots in ubiquitous computing, focusing on how they can improve and support modern lifestyles. We conducted two studies: an online survey (n=50) to understand current usage patterns of these robots within homes and an exploratory study (n=12) with HCI and HRI experts. Our thematic analysis revealed 12 key dimensions for developing interactions with domestic robots and outlined over 100 use cases, illustrating how these robots can offer proactive assistance and provide privacy. Finally, we implemented a proof-of-concept prototype to demonstrate the feasibility of reappropriating domestic robots for diverse ubiquitous computing applications.

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This paper is an invitation to HCI designers and artist-researchers to weave together practice-based ways of knowing with others’ experiences with their work, focused on understanding cognitive and aesthetic impressions garnered during exhibitions. It describes the first author's process for weaving together the warp (practice-based ways of knowing) and weft (interview-based insights into others’ experiences) by leveraging the exhibition site as a place to generate knowledge with attendees experiencing their work. Understanding others’ experiences informs the experimentation that practice-based knowledge generation is founded on, deepening and enriching the resulting work.

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This paper examined how rotary force feedback in knobs can enhance control over musical techniques, focusing on both performance and user experience. To support our study, we developed the Bend-aid system, a web-based sequencer with pre-designed haptic modes for pitch modulation, integrated with TorqueTuner, a rotary haptic device that controls pitch through programmable haptic effects. Then, twenty musically trained participants evaluated three haptic modes (No-force feedback (No-FF), Spring, and Detent) by performing a vibrato mimicry task, rating their experience on a Likert scale, and providing qualitative feedback in post-experiment interviews. The study assessed objective performance metrics (Pitch Error and Pitch Deviation) and subjective user experience ratings (Comfort, Ease of Control, and Helpfulness) of each haptic mode. User experience results showed that participants found force feedback helpful. Performance results showed that the Detent mode significantly improved pitch accuracy and vibrato stability compared to No-FF, while the Spring mode did not show a similar improvement. Post-experiment interviews showed that preferences for Spring and Detent modes varied, and the applicants provided suggestions for future knob designs. These findings suggest that force feedback may enhance both control and the experience of control in rotary knobs, with potential applications for more nuanced control in DMIs.

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We introduce Augmented Physics, a machine learning-integrated authoring tool designed for creating embedded interactive physics simulations from static textbook diagrams. Leveraging recent advancements in computer vision, such as Segment Anything and Multi-modal LLMs, our web-based system enables users to semi-automatically extract diagrams from physics textbooks and generate interactive simulations based on the extracted content. These interactive diagrams are seamlessly integrated into scanned textbook pages, facilitating interactive and personalized learning experiences across various physics concepts, such as optics, circuits, and kinematics. Drawing from an elicitation study with seven physics instructors, we explore four key augmentation strategies: 1) augmented experiments, 2) animated diagrams, 3) bi-directional binding, and 4) parameter visualization. We evaluate our system through technical evaluation, a usability study (N=12), and expert interviews (N=12). Study findings suggest that our system can facilitate more engaging and personalized learning experiences in physics education.

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Sustainable fabrication approaches and biomaterials are increasingly being used in HCI to fabricate interactive devices. However, the majority of the work has focused on integrating electronics. This paper takes a sustainable approach to exploring the fabrication of biochemical sensing devices. Firstly, we contribute a set of biochemical formulations for biological and environmental sensing with bio-sourced and environment-friendly substrate materials. Our formulations are based on a combination of enzymes derived from bacteria and fungi, plant extracts and commercially available chemicals to sense both liquid and gaseous analytes: glucose, lactic acid, pH levels and carbon dioxide. Our novel holographic sensing scheme allows for detecting the presence of analytes and enables quantitative estimation of the analyte levels. We present a set of application scenarios that demonstrate the versatility of our approach and discuss the sustainability aspects, its limitations, and the implications for bio-chemical systems in HCI.

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We explore the potential for subtle on-hand gesture and microgesture interactions for map navigation with augmented reality (AR) devices. We describe a design exercise and follow-up elicitation study in which we identified on-hand gestures for cartographic interaction primitives. Microgestures and on-hand interactions are a promising space for AR map navigation as they offers always-available, tactile, and memorable spaces for interaction. Our findings show a clear set of microgesture interaction patterns that are well suited for supporting map navigation and manipulation. In particular, we highlight how the properties of various microgestures align with particular cartographic interaction tasks. We also describe our experience creating an exploratory proof-of-concept AR map prototype which helped us identify new opportunities and practical challenges for microgesture control. Finally, we discuss how future AR map systems could benefit from on-hand and microgesture input schemes.

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We examine input visualizations, visual representations that are designed to collect (and represent) new data rather than encode preexisting datasets. Information visualization is commonly used to reveal insights and stories within existing data. As a result, most contemporary visualization approaches assume existing datasets as the starting point for design, through which that data is mapped to visual encodings. Meanwhile, the implications of visualizations as inputs and as data sources have received little attention—despite the existence of visual and physical examples stretching back centuries. In this paper, we present a design space of 50 input visualizations analyzing their visual representation, data, artifact, context, and input. Based on this, we identify input modalities, purposes of input visualizations, and a set of design considerations. Finally, we discuss the relationship between input visualization and traditional visualization design and suggest opportunities for future research to better understand these visual representations and their potential.

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We explore the potential of generative AI text-to-image models to help designers efficiently craft unique, representative, and demographically diverse anthropographics that visualize data about people. Currently, creating data-driven iconic images to represent individuals in a dataset often requires considerable design effort. Generative text-to-image models can streamline the process of creating these images, but risk perpetuating designer biases in addition to stereotypes latent in the models. In response, we outline a conceptual workflow for crafting anthropographic assets for visualizations, highlighting possible sources of risk and bias as well as opportunities for reflection and refinement by a human designer. Using an implementation of this workflow with Stable Diffusion and Google Colab, we illustrate a variety of new anthropographic designs that showcase the visual expressiveness and scalability of these generative approaches. Based on our experiments, we also identify challenges and research opportunities for new AI-enabled anthropographic visualization tools.

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The development of low-cost and non-invasive biosensors for monitoring electrochemical biomarkers in sweat holds great promise for personalized healthcare and early disease detection. In this work, we present ecSkin, a novel fabrication approach for realizing epidermal electrochemical sensors that can detect two vital biomarkers in sweat: glucose and cortisol. We contribute the synthesis of functional reusable inks, that can be formulated using simple household materials. Electrical characterization of inks indicates that they outperform commercially available carbon inks. Cyclic voltammetry experiments show that our inks are electrochemically active and detect glucose and cortisol at activation voltages of -0.36 V and -0.22 V, respectively. Chronoamperometry experiments show that the sensors can detect the full range of glucose and cortisol levels typically found in sweat. Results from a user evaluation show that ecSkin sensors successfully function on the skin. Finally, we demonstrate three applications to illustrate how ecSkin devices can be deployed for various interactive applications.

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We introduce Augmented Math, a machine learning-based approach to authoring AR explorable explanations by augmenting static math textbooks without programming. To augment a static document, our system first extracts mathematical formulas and figures from a given document using optical character recognition (OCR) and computer vision. By binding and manipulating these extracted contents, the user can see the interactive animation overlaid onto the document through mobile AR interfaces. This empowers non-technical users, such as teachers or students, to transform existing math textbooks and handouts into on-demand and personalized explorable explanations. To design our system, we first analyzed existing explorable math explanations to identify common design strategies. Based on the findings, we developed a set of augmentation techniques that can be automatically generated based on the extracted content, which are 1) dynamic values, 2) interactive figures, 3) relationship highlights, 4) concrete examples, and 5) step-by-step hints. To evaluate our system, we conduct two user studies: preliminary user testing and expert interviews. The study results confirm that our system allows more engaging experiences for learning math concepts.

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This paper introduces HoloBots, a mixed reality remote collaboration system that augments holographic telepresence with synchronized mobile robots. Beyond existing mixed reality telepresence, HoloBots lets remote users not only be visually and spatially present, but also physically engage with local users and their environment. HoloBots allows the users to touch, grasp, manipulate, and interact with the remote physical environment as if they were co-located in the same shared space. We achieve this by synchronizing holographic user motion (Hololens 2 and Azure Kinect) with tabletop mobile robots (Sony Toio). Beyond the existing physical telepresence, HoloBots contributes to an exploration of broader design space, such as object actuation, virtual hand physicalization, world-in-miniature exploration, shared tangible interfaces, embodied guidance, and haptic communication. We evaluate our system with twelve participants by comparing it with hologram-only and robot-only conditions. Both quantitative and qualitative results confirm that our system significantly enhances the level of co-presence and shared experience, compared to the other conditions.

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We introduce RealityCanvas, a mobile AR sketching tool that can easily augment real-world physical motion with responsive hand-drawn animation. Recent research in AR sketching tools has enabled users to not only embed static drawings into the real world but also dynamically animate them with physical motion. However, existing tools often lack the flexibility and expressiveness of possible animations, as they primarily support simple line-based geometry. To address this limitation, we explore both expressive and improvisational AR sketched animation by introducing a set of responsive scribble animation techniques that can be directly embedded through sketching interactions: 1) object binding, 2) flip-book animation, 3) action trigger, 4) particle effects, 5) motion trajectory, and 6) contour highlight. These six animation effects were derived from the analysis of 172 existing video-edited scribble animations. We showcase these techniques through various applications, such as video creation, augmented education, storytelling, and AR prototyping. The results of our user study and expert interviews confirm that our tool can lower the barrier to creating AR-based sketched animation, while allowing creative, expressive, and improvisational AR sketching experiences.

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We present perspectives from 10 autistic Twitch streamers regarding their experiences as livestreamers and how autism uniquely colors their experiences. Livestreaming offers a social online experience distinct from in-person, face-to-face communication, where autistic people tend to encounter challenges. Our reflexive thematic analysis of interviews with 10 participants showcases autistic livestreamers’ perspectives in their own words. Our findings center on the importance of having streamers establishing connections with other, sharing autistic identities, controlling a space for social interaction, personal growth, and accessibility challenges. In our discussion, we highlight the crucial value of having a medium for autistic representation, as well as design opportunities for streaming platforms to onboard autistic livestreamers and to facilitate livestreamers communication with their audience.

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