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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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The tongue is a remarkable human organ with a high concentration of taste receptors and an exceptional ability to sense touch. This work uses electro-tactile stimulation to explore the intricate interplay between tactile perception and taste rendering on the tongue. To facilitate this exploration, we utilized a fexible, high-resolution electro-tactile prototyping platform that can be administered in the mouth. We have created a design tool that abstracts users from the low-level stimulation parameters, enabling them to focus on higher-level design objectives. Through this platform, we present the results of three studies. Our frst study evaluates the design tool’s qualitative and formative aspects. In contrast, the second study measures the qualitative attributes of the sensations produced by our device, including tactile sensations and taste. In the third study, we demonstrate the ability of our device to sense touch input through the tongue when placed on the hard palate region in the mouth. Finally, we present a range of application demonstrators that span diverse domains, including accessibility, medical surgeries, and extended reality. These demonstrators showcase the versatility and potential of our platform, highlighting its ability to enable researchers and practitioners to explore new ways of leveraging the tongue’s unique capabilities. Overall, this work presents new opportunities to deploy tongue interfaces and has broad implications for designing interfaces that incorporate the tongue as a sensory organ.

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Despite the advances and ubiquity of digital communication media such as videoconferencing and virtual reality, they remain oblivious to the rich intentions expressed by users. Beyond transmitting audio, videos, and messages, we envision digital communication media as proactive facilitators that can provide unobtrusive assistance to enhance communication and collaboration. Informed by the results of a formative study, we propose three key design concepts to explore the systematic integration of intelligence into communication and collaboration, including the panel substrate, language-based intent recognition, and lightweight interaction techniques. We developed CrossTalk, a videoconferencing system that instantiates these concepts, which was found to enable a more fluid and flexible communication and collaboration experience.

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A growing body of work on musical haptics focuses on vibrotactile feedback, while musical applications of force feedback, though more than four decades old, are sparser. This paper reviews related work combining music and haptics, focusing on force feedback. We then discuss the limitations of these works and elicit the main challenges in current applications of force feedback and music (FF&M), which are as follows: modularity; replicability; affordability; and usability. We call for the following opportunities in future research works on FF&M: embedding audio and haptic software into hardware modules, networking multiple modules with distributed control, and authoring with audio-inspired and audio-coupled tools. We illustrate our review with recent efforts to develop an affordable, open-source and self-contained 1-Degree-of-Freedom (DoF) rotary force-feedback device for musical applications, i.e., the TorqueTuner, and to embed audio and haptic processing and authoring in module firmware, with ForceHost, and examine their advantages and drawbacks in light of the opportunities presented in the text.

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This hands-on class will allow artists to use open-source tools to create interactive and immersive experiences. These tools have been created and incubated at the Society for Arts and Technology (SAT), a unique non-profit organization in Canada whose mission is to democratize technologies to enable people to experience and author multisensory immersions. During the class we invite participants to use their favorite software on platforms they are already familiar with, to interface with our tools. The toolset will include transmission protocols, video mapping tools, sound spatialization software, and gestural control using pose detection. The class will be organized in two parts: a presentation of the tools and context involving the development and applications, and a hands-on session with an ephemeral immersive space. This event is designed for art researchers, artists, designers, content creators, and other creatives interested in creating immersive spaces using research-developed tools. Participants will learn how to employ open-source tools for different artistic tasks so that they will be able to deploy their own immersive spaces after the class.

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In this paper, we introduce Physica, a tangible physics simulation system and approach based on tabletop mobile robots. In Physica, each tabletop robot can physically represent distinct simulated objects that are controlled through an underlying physics simulation, such as gravitational force, molecular movement, and spring force. It aims to bring the benefits of tangible and haptic interaction into explorable physics learning, which was traditionally only available on screen-based interfaces. The system utilizes off-the-shelf mobile robots (Sony Toio) and an open-source physics simulation tool (Teilchen). Built on top of them, we implement the interaction software pipeline that consists of 1) an event detector to reflect tangible interaction by users, and 2) target speed control to minimize the gap between the robot motion and simulated moving objects. To present the potential for physics education, we demonstrate various application scenarios that illustrate different forms of learning using Physica. In our user study, we investigate the effect and the potential of our approach through a perception study and interviews with physics educators.

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Anthropographics are human-shaped visualizations that aim to emphasize the human importance of datasets and the people behind them. However, current anthropographics tend to employ homogeneous human shapes to encode data about diverse demographic groups. Such anthropographics can obscure important differences between groups and contemporary designs exemplify the lack of inclusive approaches for representing human diversity in visualizations. In response, we explore the creation of demographically diverse anthropographics that communicate the visible diversity of demographically distinct populations. Building on previous anthropographics research, we explore strategies for visualizing datasets about people in ways that explicitly encode diversity—illustrating these approaches with examples in a variety of visual styles. We also critically reflect on strategies for creating diverse anthropographics, identifying social and technical challenges that can result in harmful representations. Finally, we highlight a set of forward-looking research opportunities for advancing the design and understanding of diverse anthropographics.

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We present ChameleonControl, a real-human teleoperation system for scalable remote instruction in hands-on classrooms. In contrast to the existing video or AR/VR-based remote hands-on education, ChameleonControl uses a real human as a surrogate of a remote instructor. Building on existing human-based telepresence approaches (e.g. ChameleonMask), we contribute a novel method to teleoperate a human surrogate through synchronized mixed reality (MR) hand gestural navigation and verbal communication. By overlaying the remote instructor's virtual hands in the local user's MR view, the remote instructor can guide and control the local user as if they were physically present. This allows the local user/surrogate to synchronize their hand movements and gestures with the remote instructor, effectively ``teleoperating'' a real human. We evaluate our system through the in-the-wild deployment for physiotherapy classrooms, as well as lab-based experiments for other application domains such as mechanical assembly, sign language, and cooking lessons. The study results confirm that our approach can increase engagement and the sense of co-presence, showing potential for the future of remote hands-on classrooms.

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This paper introduces Teachable Reality, an augmented reality (AR) prototyping tool for creating interactive tangible AR applications with arbitrary everyday objects. Teachable Reality leverages vision-based interactive machine teaching (e.g., Teachable Machine), which captures real-world interactions for AR prototyping. It identifies the user-defined tangible and gestural interactions using an on-demand computer vision model. Based on this, the user can easily create functional AR prototypes without programming, enabled by a trigger-action authoring interface. Therefore, our approach allows the flexibility, customizability, and generalizability of tangible AR applications that can address the limitation of current marker-based approaches. We explore the design space and demonstrate various AR prototypes, which include tangible and deformable interfaces, context-aware assistants, and body-driven AR applications. The results of our user study and expert interviews confirm that our approach can lower the barrier to creating functional AR prototypes while also allowing flexible and general-purpose prototyping experiences.

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We contribute interaction techniques for augmenting mixed reality (MR) visualizations with smartphone proxies. By combining head-mounted displays (HMDs) with mobile touchscreens, we can augment low-resolution holographic 3D charts with precise touch input, haptics feedback, high-resolution 2D graphics, and physical manipulation. Our approach aims to complement both MR and physical visualizations. Most current MR visualizations suffer from unreliable tracking, low visual resolution, and imprecise input. Data physicalizations on the other hand, although allowing for natural physical manipulation, are limited in dynamic and interactive modification. We demonstrate how mobile devices such as smartphones or tablets can serve as physical proxies for MR data interactions, creating dynamic visualizations that support precise manipulation and rich input and output. We describe 6 interaction techniques that leverage the combined physicality, sensing, and output capabilities of HMDs and smartphones, and demonstrate those interactions via a prototype system. Based on an evaluation, we outline opportunities for combining the advantages of both MR and physical charts.

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This paper introduces VR Haptics at Home, a method of repurposing everyday objects in the home to provide casual and on-demand haptic experiences. Current VR haptic devices are often expensive, complex, and unreliable, which limits the opportunities for rich haptic experiences outside research labs. In contrast, we envision that, by repurposing everyday objects as passive haptics props, we can create engaging VR experiences for casual uses with minimal cost and setup. To explore and evaluate this idea, we conducted an in-the-wild study with eight participants, in which they used our proof-of-concept system to turn their surrounding objects such as chairs, tables, and pillows at their own homes into haptic props. The study results show that our method can be adapted to different homes and environments, enabling more engaging VR experiences without the need for complex setup process. Based on our findings, we propose a possible design space to showcase the potential for future investigation.

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We present LivePose: an open-source (GPL license) tool that democratizes pose detection for multimedia arts and telepresence applications, optimized for and distributed on open edge devices. We designed the architecture of LivePose with a 5-stage pipeline (frame capture, pose estimation, dimension mapping, filtering, output) sharing streams of data flow, distributable on networked nodes. We distribute LivePose and dependencies packages and filesystem images optimized for edge devices (NVIDIA Jetson). We showcase multimedia arts and telepresence applications enabled by LivePose.

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