Facial interaction provides a safe, hands-free input method for cyclists. However, existing wearable facial gesture recognition suffers from severe interference in real-world conditions such as lighting, vibration, sweat, noise, and temperature changes. We present MagFace, an interference-resistant recognition system for cycling glasses using energy-efficient magnetic sensing. MagFace employs four pairs of magnetic silicone and magnetometers on the frame to capture subtle facial skin movements, operating at 30 Hz with a peak power of 150 mW. A tailored deep learning pipeline effectively learns magnetic signals for gesture classification. An evaluation (N=15) shows that MagFace required only one minute of training data to recognize six gestures across different cycling scenarios with high accuracy. A controlled conditions evaluation (N=8) shows MagFace’s robustness against strong lighting, wind, bumpy roads, and uphills. Finally, an in-the-wild evaluation (N=14) shows the stable performance of MagFace’s real-time system and demonstrates promising usability of MagFace.

We present VibMotion, which enables programmable locomotion under vibration excitation through customizable 3D-printed structures. VibMotion employs a G-code–controlled 3D printing process to fabricate directional, asymmetric hook-shaped geometries that leverage surface interactions to translate vibration excitation into stable motion behaviors without complex control. Through exploratory studies on a standardized motion module, we investigate how geometric orientation and arrangement influence locomotion outcomes under vibration, demonstrating multiple motion patterns including directional translation, turning, rotation, and hopping. By modularly combining these motion units, more complex motion behaviors can be composed from simple structural elements, expanding the design space of programmable morphology for interactive motion systems and playful embodied interaction.

While milli-scale shape-changing interfaces hold immense potential for wearables, current fabrication methods remain inaccessible to most designers. We introduce HygroFold, a democratized approach for prototyping milli-scale actuators with milli-scale features (down to 100 µm hinge width). By patterning hydrophobic toner onto hydrophilic cellophane, we achieve precise bilayer actuation using only a laser printer and a laminator. Unlike prior works that rely on liquid water or high-humidity chambers, HygroFold is sensitive enough to be powered by transient body vapor, responding to exhalation or resting skin humidity, such as insensible perspiration on hand. This paper details the low-cost fabrication process and presents a suite of miniaturized on-skin interfaces, demonstrating how subtle physiological signals can be translated into expressive physical interactions.

While tangible and embodied interfaces have been explored in the intersectional field of HCI and choreography, choreographic ideas through material and bodily interaction have received limited attention. Using the snap-through bistability of inflatable structures in wearable design for dance—enabled by their capabilities for rapid shape reconfiguration, self-sensing, actuation, and enhanced tactile feedback—we explore a novel choreographic experience. In this poster, we present a pilot study of how choreographers interact with physical choreographic tools that embody specific material and structural properties. We examine how tangible choreographic interfaces can record, inspire, and convey choreographic information. Furthermore, we discuss how performative tools can transcend their functional role to become actors within the performance context.

Wood has become increasingly applied in shape-changing interfaces for its eco-friendly and smart responsive properties, while its applications face challenges as it remains primarily driven by humidity. We propose TH-Wood, a biodegradable actuator system composed of wood veneer and microbial polymers, driven by both temperature and humidity, and capable of functioning in complex outdoor environments. This dual-factor-driven approach enhances the sensing and response channels, allowing for more sophisticated coordinating control methods. To assist in designing and utilizing the system more effectively, we developed a structure library inspired by dynamic plant forms, conducted extensive technical evaluations, created an educational platform accessible to users, and provided a design tool for deformation adjustments and behavior previews. Finally, several ecological applications demonstrate the potential of TH-Wood to significantly enhance human interaction with natural environments and expand the boundaries of human-nature relationships.

We present KiriInflate, a rapid, precise, and accessible fabrication method for creating stretchable inflatables with Kirigami structures. These inflatables, fabricated at multiple scales (from fingernail-sized to body-sized), exhibit rapid, large contraction upon inflation up to 83.5% and provide tunable stretchability. Our fabrication process leverages the electrostatic adhesion of plastic films and an off-the-shelf laser cutter to simultaneously cut and fuse the edges of inflatables, achieving ultra-narrow seals (< 0.125 mm). Our structural design enables versatile 3D morphing upon inflation and tunable stretch behavior, with experimental studies offering design guidelines for key geometric parameters. A series of applications, including an eyelid assistive device, a multi-mode game handle, a dynamic elbow brace, and breathable lamps, highlight its potential for diverse interaction in HCI.

Shape-changing interfaces use physical changes of shape as input or output to convey information, and interact with users. Plants are natural shape-changing interfaces, expert in adjusting their shape or modality to adapt to the environment. In this paper, plant-derived natural shape-changing phenomena are systematically analyzed. Then, several corresponding plant-inspired design strategies for shape-changing interfaces are summarized with recent advancements including material selections and syntheses, fabrication methods, and actuating mechanisms. Practical applications across diverse domains aim to prove the advantages and potential of plant-inspired shape-changing interfaces in agriculture, healthcare, architecture, robotics, etc. Furthermore, the opportunities and challenges are also discussed, such as design thinking in interdisciplinary tasks, dynamic behavior and control principles, novel materials and processes, application scenario and functionality matching, and large-scale application requirements. This paper is expected to inspire in-depth research on plant-inspired shape-changing interfaces.

Diametrically magnetized circular magnets are widely used in electromechanical systems, where accurate analysis of their mechanical properties is crucial for predicting responses and designing system structures. This paper proposes an approach to calculate the interacting magnetic forces of circular permanent magnets with diametrical magnetization, encompassing cylindrical and ring magnets, based on equivalent magnetizing current model. The paper provides a detailed formulation for magnetic field and force. The accuracy of the calculation results is validated through experimental measurements. The results also show richer variations in the behaviors of interacting forces between diametrical ring magnets. This study expands the selection of magnetic force calculation methods for researchers and engineers. Furthermore, the diverse behaviors identified can bring new insights for the application of diametrically magnetized circular magnets in electromechanical systems and frontier field.

Textile stretch sensors offer significant potential for motion tracking in human-computer interaction, yet designing precise sensor layouts remains challenging due to variable skin deformation patterns and manual design dependencies. We present Laytex, a data-driven tool that automates sensor layout generation through body deformation analysis and clustering-based optimization. The system processes 3D point cloud data to identify deformation hotspots, supports parametric customization of sensor quantities and lengths, and visualizes layouts with coverage reports. Evaluations with 10 participants performing shoulder motions demonstrated strong sensor-angle correlations (mean maximum coefficient: 0.76) and effective angles interpretation using LSTM networks (Mean Per-Joint Angular Error: 7.65 degrees), comparable to state-of-the-art manually designed solutions. A workshop with 19 participants from diverse backgrounds further validated Laytex's cross-domain applicability and ability to streamline workflows, resulting in functional prototypes across applications. Laytex bridges the gap between computational design and practical deployment, offering a scalable solution for developing adaptive wearable technologies.

We propose EmbroChet, a hybrid approach that bridges digital fabrication and textile craftsmanship, empowering individuals unfamiliar with intricate craft techniques to design and fabricate 3D textile handicrafts intuitively. EmbroChet allows the creation of handicrafts by embroidering chain stitches (a fundamental embroidery technique) onto a heat-shrinkable film, which subsequently self-transforms from a 2D composite to a 3D textile through a freely controllable heating triggering process. Through a single stitch type, the method enables custom designs and intricate geometries to be achieved without complex manual skills that often requires expertise between different stitch knowledge. To better demonstrate EmbroChet, we propose a design tool that includes shape-changing libraries to assist users in customizing 3D shapes. The evaluation demonstrates its unique strength in balancing geometric complexity and textile softness. Furthermore, our workshop verifies the feasibility of EmbroChet, exploring its potential for personalized textile fabrication, and synergizing the precision of digital fabrication with the tactile artistry of textile craftsmanship.

Nightmares can adversely affect individuals' mental health and well-being, necessitating timely psychological intervention. Current nightmare therapy has set high requirements for therapists, appeared abstract to clients, and showed poor interaction between them, due to its extensive information input, lack of sensory stimulation, and exclusive reliance on one-on-one conversation. We propose DreamDirector, a visual-interactive and narrative generative system powered by generative AI. Based on Imagery Rehearsal Therapy (IRT) and Nightmare Deconstruction and Reprocessing (NDR), the system can (1) recollect the nightmare scene, (2) interpret the dream with LLM, (3) reprocess the nightmare by generating therapeutic dream visuals using AI painting alongside meditative texts, and feedback with a picture book. Finally, we verified the usability of this system in terms of efficiency enhancement and interaction promotion through a user study with 2 therapists and 16 clients. The results revealed emotional relief among clients, with a positive and impressive attitude toward visual interaction.

In the realm of digital fabrication, skeletal structures offer lightweight, cost-effective solutions for art installation, rapid fabrication, and large-scale construction. However, existing 3D printing methods for skeletal structures often require support structures, resulting in prolonged print time and excessive material consumption. This paper presents Touch-n-Curl, a design and construction system for rapidly prototyping 3D skeletal curved structures, covering scales from millimeters to meters, by printing 2D zipper assemblies with interlocking mechanisms using conventional 3D printers. This design process is made possible by a computational method that unrolls a 3D model into a 2D branch assembly while minimizing branch intersections, making the fabrication process both efficient and robust. A parametric design tool is developed to support this inverse design workflow, instantly generating 2D zippers and offering a preview of the 3D skeletal assembly. To ensure users can effectively utilize the system, we implement methods such as edge disjoining and tree rectification to accommodate closed mesh imports in addition to opened trees at a wide range of complexity measured by curvature and torsion. The result of this integrated and accessible workflow is evaluated in fabrication speed, mechanical strength, and shape-matching accuracy, and its versatility is showcased through a series of demonstrations.

Aridity has serious impacts on the pools, fluxes and processes of terrestrial carbon (C) and nitrogen (N) cycles. Drylands, with high aridity, also being particularly sensitive to global shifts, require accurate estimation of soil organic carbon (SOC) and total nitrogen (STN) pools for a comprehensive grasp of dryland C and N dynamics within the global C and N cycle. Hence, SOC and STN of 2895 soil samples combined with 11 selected environmental covariates were collected from 175 sampling sites in the drylands of China, the spatial distributions of SOC density (SOCD) and STN density (STND) were mapped with best-performing random forest model. SOC0- 100cm and STN 0-100cm stocks were 30.84 and 2.02 Pg, respectively. Mean annual precipitation and soil moisture were identified as the primary drivers of SOCD 0-30cm and STND 0-30cm , while mean annual temperature influenced SOCD 30-50cm and STND 30-50cm , and soil clay content affected SOCD 50-100cm and STND 50-100cm . Future warming is projected to reduce both SOCD and STND, whereas increased precipitation is expected to have a positive effect on both variables in drylands. Under future climate scenarios outlined by the Representative Concentration Pathway, declines in both SOCD and STND are anticipated, with STND exhibiting a more pronounced decrease. A 1.5 degrees C increase in temperature had the greatest effect on SOCD, while a 15 % decrease in precipitation had the greatest effect on STND. In conclusion, the spatiotemporal estimations presented in this study serve as a valuable supplement to existing SOC and STN stock measurements, enhancing our understanding of C and N cycling in drylands. Our findings are instrumental for effective C and N sinks management, providing valuable data for informed decision-making. For example, afforestation in drylands can lead to significant increases in soil C and N stocks. However, In the future, further warming may lead to large losses of soil C and N in drylands.

Filigree art, which represents typical intricate metalwork, has been captivating audiences worldwide with its delicate lace-like patterns and interwoven metal wires’ refined aesthetics. Particularly, Chinese Intangible Cultural Heritage filigree craftsmanship has a unique aesthetic value in fine patterns and complex three-dimensional shapes. However, designing and creating filigree artworks is a labor-intensive and technically complex task and often requires extensive training and a deep understanding of the craft, which limits its design aesthetic and cultural continuity. Aiming to overcome these challenges, this study proposes an artificial intelligence (AI) -aided method that uses AI-generated content (AIGC) technology to accelerate the visualization process of this time-consuming and intricate craft by investigating the role of AI in craft design. First, a comprehensive study of filigree art culture is conducted to identify more than ten historic filigree techniques to obtain AI opportunities. Then, an AI-powered framework called AIFiligree is developed by optimizing culture-based labels and training parameters, enabling the generation of highly authentic fine filigree structures. Further, user workflows are introduced to support diverse design scenarios. Through user studies involving 22 filigree experts and 16 designers, we finally gained insights into AI’s opportunities and challenges in cultural learning, expression, and design.

Desktop 3D printers are capable of fabricating structures with complex geometries, thus enhancing the functionality and interactivity of printed objects. Peelable structures represent an important application in 3D printing, as the supports and brims demonstrate, offering more possibilities for printing. However, existing tools are limited in their ability to effectively assist users in designing and customizing such structures, and their broader application potential remains underexplored. In traditional artistic practices, masks also exhibit the characteristics of a peelable design and serve as creative tools. However, within the field of human-computer interaction, no prior work has investigated the use of 3D-printed peelable structures for mask creation. To address this gap, we present PeelFab, a fabrication method and accompanying design tool for generating custom peelable structures directly within modeling software. Through the use of a built-in structure library and an interactive interface, users can create peelable structures based on points, lines, and surfaces, allowing the design of various 3D printed masking geometries. We also demonstrate several application cases that showcase the potential of 3D-printed masking using peelable structures.

In recent years, the wearable motion capture technology has been developed rapidly in various applications. However, conventional methods usually emphasize capturing the whole body skeleton or limb movements, without considering the personalized human body data and fine-grained deformation information. Thus, it is important to develop a proper wearable motion and deformation capture system based on the personalized human body data to provide people with more customized and immersive experiences. In this paper, a rapid and scalable construction method of the wearable inertial measurement unit (IMU) sensor network is proposed to generate personalized wearable solutions for people with different body types. Additionally, a robust self-sensing algorithm based on the IMU sensor network is proposed to reconstruct not only the whole body or limb movements but also the fine-grained muscle deformations. To validate the performance, we evaluate the accuracy and robustness of our method. In the accuracy evaluation, the average measurement error is 3.90mm, less than 1.80% of the test model size (180mm × 150mm × 72mm). In the robustness evaluation, the average measurement error is 6.15mm. Finally, an application on personalized arm motion and deformation capture demonstrates the feasibility and applicability of the proposed self-sensing IMU sensor network.

We present GyFoam, a fabrication method integrating foam material with lattice structure to enable controlled and uniform expansion, which supports high-quality forming in appearance and customizable stiffness in function, using standard 3D printers, filaments, commercially available Thermo-Expandable Microspheres and silicone. To achieve customizable stiffness, we propose two methods: modifying material concentration and adjusting lattice structural parameters. Additionally, we propose three shape control strategies for creating complex shapes: bending, wavy edges, and internal doming. Furthermore, a user-friendly design tool is established for users to construct lattice structures, preview basic deformation, and generate mold models for printing. Finally, through a series of applications, we validate GyFoam’s practical usage of fabricating large objects, wearable products, enabling flexible interactions and creating aesthetic designs.

Biomimicry, a methodology adapted from nature, always inspires optimum solutions and innovative technologies in human history. To get children interested in, excited about, and inspired by biomimicry, we introduce KiPneu, a robotic platform that facilitates biomimicry education through hands-on, solution-oriented learning and a digital learning environment. KiPneu allows children to mimic flexible animal locomotion, like fish swimming or worm squirming, using low-cost building blocks and non-electrical pneumatic actuators. We provide five types of non-electrical tangible valves to adjust robot motion characteristics, such as direction and speed, through engaging tangible programming. Additionally, to facilitate the whole learning process, KiPneu comes with interactive instructional interface that visualize and simulate the pneumatic system. To validate KiPneu’s educational efficacy, we conducted a three-day workshop with 21 children aged 5-12. Pre-and-post surveys revealed KiPneu not only enhanced their understanding of animal locomotion mechanisms but also spurred interest in creative construction using acquired knowledge.

Independent travel is crucial for the socialization of visually impaired teenagers but is deficient in current Orientation and Mobility education from school for the blind. We developed MyWay, a modular 3D transportation learning kit, through a co-designing process with both experts and students from a school for the blind. MyWay consists of modules with Braille and tactile paving, coupled with spatial audio differentiated into information, environment, and explanation. With these realistic modules, we can build complex multi-layered spatial public transportation scenarios (e.g., taking a bus, hailing a taxi, and riding a subway) to facilitate comprehension of transportation infrastructure and provide directional guidance. We evaluate MyWay through a three-round evaluation with 25 participants from school for the blind. Our findings reveal how the tangible learning process assists teenagers in comprehending transit regulations, what hinders and how to improve their spatial cognition, familiarity and courage with independent travel.

In tangible irreversible human-machine interactions (HMIs), erroneous inputs resulting from users' unfamiliarity, inattention, or ingrained habits can lead to unintended consequences. Although some design measures like buttons with protective shells or safety switches before critical actions have been implemented to minimize human errors in both everyday products and industrial interfaces, a cohesive guiding strategy on when, where, and how to prevent unintended consequences is lacking. Inspired by the confirmation dialog boxes commonly utilized in graphical user interfaces, this study proposes design strategies for effective tangible confirmation behaviors in HMIs. Initially, a workshop was conducted to gather design cases and explore potential design opportunities in future scenarios. By analysing the outcomes, we propose an evaluation method for assessing the necessity and complexity requirements of confirmation design and introduce a design library considering complexity levels graded by users' time, effort, and cognitive load expenditure. Subsequently, a user behavior experiment was conducted to validate the feasibility and efficacy of the proposed strategies. Our strategies offer valuable references for designers, highlighting the significance of confirmation design in preventing human errors. Following these strategies, designers and engineers can integrate more Kansai engineering principles into HMIs to ensure user safety, protect property, and enhance interaction efficiency.