IntelliLining: Activity Sensing through Textile Interlining Sensors Using TENGsWe 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.2025MEMahdie Ghane Ezabadi et al.Simon Fraser University, Computing ScienceHaptic WearablesElectronic Textiles (E-textiles)CHI
Laser-Powered Vibrotactile RenderingSu 等人提出激光触觉渲染技术，利用激光在皮肤表面产生热振感，实现无接触触觉反馈，为 VR/AR 提供新型交互方案。2024YSYuning Su et al.Mid-Air Haptics (Ultrasonic)UbiComp
RElectrode: A Reconfigurable Electrode For Compound Sensing Based on MicrofluidicsIn this paper, we propose a reconfigurable electrode, RElectrode, using a microfluidic technique that can change the geometry and material properties of the electrode to satisfy the needs for sensing a variety of different types of user input through touch/touchless gestures, pressure, temperature, and distinguish between different types of objects or liquids. Unlike the existing approaches, which depend on specific-shaped electrode for particular sensing (e.g., coil for inductive sensing), RElectrode enables capacity, inductance, resistance/pressure, temperature, pH sensings all in a single package. We demonstrate the design and fabrication of the microfluidic structure of our RElectrode, evaluate its sensing performance through several studies, and provide some unique applications. RElectrode demonstrates technical feasibility and application values of integrating physical and biochemical properties of microfluidics into novel sensing interfaces.2021WSWei Sun et al.Institute of Software Chinese Academy of SciencesIn-Vehicle Haptic, Audio & Multimodal FeedbackVibrotactile Feedback & Skin StimulationForce Feedback & Pseudo-Haptic WeightCHI
AccessibleCircuits: Adaptive Add-On Circuit Components for People with Blindness or Low VisionIn this paper, we propose the designs for low cost and 3D-printable add-on components to adapt existing breadboards, circuit components and electronics tools for users with blind or low vision (BLV). Through an initial user study, we identified several barriers to entry for beginners with BLV in electronics and circuit prototyping. These barriers guided the design and development of our add-on components. We focused on developing adaptations that provide additional information about the specific component pins and breadboard holes, modify tools to make them easier to use for users with BLV, and expand non-visual feedback (e.g., audio, tactile) for tasks that require vision. Through a second user study, we demonstrated that our adaptations can effectively overcome the accessibility barriers in breadboard circuit prototyping.2021RCRuei-Che Chang et al.Dartmouth CollegeMotor Impairment Assistive Input TechnologiesCircuit Making & Hardware PrototypingCHI
BackSwipe: Back-of-device Word-Gesture Interaction on SmartphonesBack-of-device interaction is a promising approach to interacting on smartphones. In this paper, we create a back-of-device command and text input technique called BackSwipe, which allows a user to hold a smartphone with one hand, and use the index finger of the same hand to draw a word-gesture anywhere at the back of the smartphone to enter commands and text. To support BackSwipe, we propose a back-of-device word-gesture decoding algorithm which infers the keyboard location from back-of-device gestures, and adjusts the keyboard size to suit the gesture scales; the inferred keyboard is then fed back into the system for decoding. Our user study shows BackSwipe is feasible and a promising input method, especially for command input in the one-hand holding posture: users can enter commands at an average accuracy of 92% with a speed of 5.32 seconds/command. The text entry performance varies across users. The average speed is 9.58 WPM with some users at 18.83 WPM; the average word error rate is 11.04% with some users at 2.85%. Overall, BackSwipe complements the extant smartphone interaction by leveraging the back of the device as a gestural input surface.2021WCWenzhe Cui et al.Stony Brook UniversityFoot & Wrist InteractionCHI
Project Tasca : Enabling Touch and Contextual Interactions with a Pocket-based Textile SensorWe present Project Tasca, a pocket-based textile sensor that detects user input and recognizes everyday objects that a user carries in the pockets of a pair of pants (e.g., keys, coins, electronic devices, or plastic items). By creating a new fabric-based sensor capable of detecting in-pocket touch and pressure, and recognizing metallic, non-metallic, and tagged objects inside the pocket, we enable a rich variety of subtle, eyes-free, and always-available input, as well as context-driven interactions in wearable scenarios. We developed our prototype by integrating four distinct types of sensing methods, namely: inductive sensing, capacitive sensing, resistive sensing, and NFC in a multi-layer fabric structure into the form factor of a jeans pocket. Through a ten-participant study, we evaluated the performance of our prototype across 11 common objects including hands, 8 force gestures, and 30 NFC tag placements. We yielded 92.3% personal cross-validation accuracy for object recognition, 96.4% accuracy for gesture recognition, and 100% accuracy for detecting NFC tags at close distance . We concluded by demonstrating the interactions enabled by our pocket-based sensor in several applications.2021TWTe-Yen Wu et al.Microsoft Research, Dartmouth CollegeHaptic WearablesFoot & Wrist InteractionContext-Aware ComputingCHI
We Can Do More to Save Guqin: Design and Evaluate Interactive Systems to Make Guqin More Accessible to the General PublicGuqin is a plucked seven-string traditional Chinese musical instrument that exists for over 3,000 years. However, as an Intangible World Cultural Heritage, the inheritance of Guqin and its culture in modern society is in deep danger. According to our study with 1,006 Chinese worldwide, Guqin as an instrument is not well-known and barely accessible. To better promote Guqin, we developed two interactive systems: VirGuqin and MRGuqin. VirGuqin was developed using a low-cost motion tracking device and was tested in a museum. 89\% of 308 participants expressed an increase in interest in learning Guqin after using our system. MRGuqin was developed as a mixed reality learning environment to reduce the entry barrier to Guqin, and was tested by 16 participants, allowing them to learn Guqin significantly faster and perform better than the current practice. Our study demonstrates how technology can be used to help the inheritance of this dying art.2021MYMinjing Yu et al.Tianjin UniversityMuseum & Cultural Heritage DigitizationInteractive Narrative & Immersive StorytellingCHI
Capacitivo: Contact-Based Object Recognition on Interactive Fabrics using Capacitive Sensing We present Capacitivo, a contact-based object recognition technique developed for interactive fabrics, using capacitive sensing. Unlike prior work that has focused on metallic objects, our technique recognizes non-metallic objects such as food, different types of fruits, liquids, and other types of objects that are often found around a home or in a workplace. To demonstrate our technique, we created a prototype composed of a 12 x 12 grid of electrodes, made from conductive fabric attached to a textile substrate. We designed the size and separation between the electrodes to maximize the sensing area and sensitivity. We then used a 10-person study to evaluate the performance of our sensing technique using 20 different objects, which yielded a 94.5% accuracy rate. We conclude this work by presenting several different application scenarios to demonstrate unique interactions that are enabled by our technique on fabrics.2020TWTe-Yen Wu et al.Haptic WearablesShape-Changing Interfaces & Soft Robotic MaterialsCircuit Making & Hardware PrototypingUIST
HapLinkage: Prototyping Haptic Proxies for Virtual Hand Tools Using Linkage MechanismHaptic simulation of hand tools like wrenches, pliers, scissors and syringes are beneficial for finely detailed skill training in VR, but designing for numerous hand tools usually requires an expert-level knowledge of specific mechanism and protocol. This paper presents HapLinkage, a prototyping framework based on linkage mechanism, that provides typical motion templates and haptic renderers to facilitate proxy design of virtual hand tools. The mechanical structures can be easily modified, for example, to scale the size, or to change the range of motion by selectively changing linkage lengths. Resistant, stop, release, and restoration force feedback are generated by an actuating module as part of the structure. Additional vibration feedback can be generated with a linear actuator. HapLinkage enables easy and quick prototypting of hand tools for diverse VR scenarios, that embody both of their kinetic and haptic properties. Based on interviews with expert designers, it was confirmed that HapLinkage is expressive in designing haptic proxy of hand tools to enhance VR experiences. It also identified potentials and future development of the framework.2020NLNianlong Li et al.Force Feedback & Pseudo-Haptic WeightHaptic WearablesShape-Changing Interfaces & Soft Robotic MaterialsUIST
Fabriccio: Touchless Gestural Input on Interactive FabricsWe present Fabriccio, a touchless gesture sensing technique developed for interactive fabrics using Doppler motion sensing. Our prototype was developed using a pair of loop antennas (one for transmitting and the other for receiving), made of conductive thread that was sewn onto a fabric substrate. The antenna type, configuration, transmission lines, and operating frequency were carefully chosen to balance the complexity of the fabrication process and the sensitivity of our system for touchless hand gestures, performed at a 10 cm distance. Through a ten-participant study, we evaluated the performance of our proposed sensing technique across 11 touchless gestures as well as 1 touch gesture. The study result yielded a 92.8% cross-validation accuracy and 85.2% leave-one-session-out accuracy. We conclude by presenting several applications to demonstrate the unique interactions enabled by our technique on soft objects.2020TWTe-Yen Wu et al.Dartmouth CollegeHaptic WearablesHand Gesture RecognitionElectronic Textiles (E-textiles)CHI
ThreadSense: Locating Touch on an Extremely Thin Interactive ThreadWe propose a new sensing technique for one-dimensional touch input workable on an interactive thread of less than 0.4 mm thick. Our technique locates up to two touches using impedance sensing with a spacing resolution unachievable by the existing methods. Our approach is also unique in that it locates a touch based on a mathematical model describing the change in thread impedance in relation to the touch locations. This allows the system to be easily calibrated by the user touching a known location(s) on the thread. The system can thus quickly adapt to various environmental settings and users. A system evaluation showed that our system could track the slide motion of a finger with an average error distance of 6.13 mm and 4.16 mm using one and five touches for calibration, respectively. The system could also distinguish between single touch and two concurrent touches with an accuracy of 99% and could track two concurrent touches with an average error distance of 8.55 mm. We demonstrate new interactions enabled by our sensing approach in several unique applications.2020PKPin-sung Ku et al.Dartmouth College; National Taiwan UniversityHaptic WearablesShape-Changing Interfaces & Soft Robotic MaterialsCHI
Exploring Eyes-free Bezel-initiated Swipe on Round SmartwatchesBezel-based gestures expand the interaction space of touch-screen devices (e.g., smartphones and smartwatches). Existing works have mainly focused on bezel-initiated swipe (BIS) on square screens. To investigate the usability of BIS on round smartwatches, we design six different circular bezel layouts, by dividing the bezel into 6, 8, 12, 16, 24, and 32 segments. We evaluate the user performance of BIS on these layouts in an eyes-free situation. The results show that the performance of BIS is highly orientation dependent, and varies significantly among users. Using the Support-Vector-Machine (SVM) model significantly increases the accuracy on 6-, 8-, 12-, and 16-segment layouts. We then compare the performance of personal and general SVM models, and find that personal models significantly improve the accuracy for 8-, 12-, 16-, and 24-segment layouts. Lastly, we discuss the potential smartwatch applications enabled by the BIS.2020PWPui Chung Wong et al.City University of Hong KongFoot & Wrist InteractionSmartwatches & Fitness BandsCHI
BiTipText: Bimanual Eyes-Free Text Entry on a Fingertip KeyboardWe present a bimanual text input method on a miniature fingertip keyboard, that invisibly resides on the first segment of a user's index finger on both hands. Text entry can be carried out using the thumb-tip to tap the tip of the index finger. The design of our keyboard layout followed an iterative process, where we first conducted a study to understand the natural expectation of the handedness of the keys in a QWERTY layout for users. Among a choice of 67,108,864 design variations, we identified 1295 candidates offering a good satisfaction for user expectations. Based on these results, we computed an optimized bimanual keyboard layout, while considering the joint optimization problems of word ambiguity and movement time. Our user evaluation revealed that participants achieved an average text entry speed of 23.4 WPM.2020ZXZheer Xu et al.Dartmouth CollegeFoot & Wrist InteractionMotor Impairment Assistive Input TechnologiesCHI
TangibleCircuits: An Interactive 3D Printed Circuit Education Tool for People with Visual ImpairmentsWe present a novel haptic and audio feedback device that allows blind and visually impaired (BVI) users to understand circuit diagrams. TangibleCircuits allows users to interact with a 3D printed tangible model of a circuit which provides audio tutorial directions while being touched. Our system comprises an automated parsing algorithm which extracts 3D printable models as well as an audio interfaces from a Fritzing diagram. To better understand the requirements of designing technology to assist BVI users in learning hardware computing, we conducted a series of formative inquiries into the accessibility limitations of current circuit tutorial technologies. In addition, we derived insights and design considerations gleaned from conducting a formal comparative user study to understand the effectiveness of TangibleCircuits as a tutorial system. We found that BVI users were better able to understand the geometric, spatial and structural circuit information using TangibleCircuits, as well as enjoyed learning with our tool.2020JDJosh Urban Davis et al.Dartmouth CollegeElectrical Muscle Stimulation (EMS)Visual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)Special Education TechnologyCHI
Zippro: The Design and Implementation of An Interactive ZipperZippers are common in a wide variety of objects that we use daily. This work investigates how we can take advantage of such common daily activities to support seamless interaction with technology. We look beyond simple zipper-sliding interactions explored previously to determine how to weave foreground and background interactions into a vocabulary of natural usage patterns. We begin by conducting two user studies to understand how people typically interact with zippers. The findings identify several opportunities for zipper input and sensing, which inform the design of Zippro, a self-contained prototype zipper slider, which we evaluate with a standard jacket zipper. We conclude by demonstrating several applications that make use of the identified foreground and background input methods.2020PKPin-sung Ku et al.Dartmouth College & National Taiwan UniversityShape-Changing Interfaces & Soft Robotic MaterialsCHI
EarTouch: Facilitating Smartphone Use for Visually Impaired People in Mobile and Public ScenariosInteracting with a smartphone using touch input and speech output is challenging for visually impaired people in mobile and public scenarios, where only one hand may be available for input (e.g., while holding a cane) and using the loudspeaker for speech output is constrained by environmental noise, privacy, and social concerns. To address these issues, we propose EarTouch, a one-handed interaction technique that allows the users to interact with a smartphone using the ear to perform gestures on the touchscreen. Users hold the phone to their ears and listen to speech output from the ear speaker privately. We report how the technique was designed, implemented, and evaluated through a series of studies. Results show that EarTouch is easy, efficient, fun and socially acceptable to use.2019RWRuolin Wang et al.Tsinghua University & Ministry of EducationFoot & Wrist InteractionDeaf & Hard-of-Hearing Support (Captions, Sign Language, Vibration)CHI
Aarnio: Passive Kinesthetic Force Output for Foreground Interactions on an Interactive ChairWe propose a new type of haptic output for foreground interactions on an interactive chair, where input is carried out explicitly in the foreground of the user's consciousness. This type of force output restricts a user's motion by modulating the resistive force when rotating a seat, tilting the backrest, or rolling the chair. These interactions are useful for many applications in a ubiquitous computing environment, ranging from immersive VR games to rapid and private query of information for people who are occupied with other tasks (e.g. in a meeting). We carefully designed and implemented our proposed haptic force output on a standard office chair and determined the recognizability of five force profiles for rotating, tilting, and rolling the chair. We present the result of our studies, as well as a set of novel interaction techniques enabled by this new force output for chairs.2019STShan-Yuan Teng et al.National Taiwan UniversityForce Feedback & Pseudo-Haptic WeightImmersion & Presence ResearchUbiquitous ComputingCHI
CircuitStyle: A System for Peripherally Reinforcing Best Practices in Hardware ComputingInstructors of hardware computing face many challenges including maintaining awareness of student progress, allocating their time adequately between lecturing and helping individual students, and keeping students engaged even while debugging problems. Based on formative interviews with 5 electronics instructors, we found that many circuit style behaviors could help novice users prevent or efficiently debug common problems. Drawing inspiration from the software engineering practice of coding style, these circuit style behaviors consist of best-practices and guidelines for implementing circuit prototypes that do not interfere with the functionality of the circuit, but help a circuit be more readable, less error-prone, and easier to debug. To examine if these circuit style behaviors could be peripherally enforced, aid an in-person instructor’s ability to facilitate a workshop, and not monopolize instructor’s attention, we developed CircuitStyle, a teaching aid for in-person hardware computing workshops. To evaluate the effectiveness of our tool, we deployed our system in an in-person maker-space workshop. The instructor appreciated CircuitStyle’s ability to provide a broad understanding of the workshop’s progress and the potential for our system to help instructors of various backgrounds better engage and understand the needs of their classroom.2019JDJosh Urban Davis et al.Game AccessibilityProgramming Education & Computational ThinkingCircuit Making & Hardware PrototypingUIST
AutoFritz: Autocomplete for Prototyping Virtual Breadboard CircuitsWe propose autocomplete for the design and development of virtual breadboard circuits using software prototyping tools. With our system, a user inserts a component into the virtual breadboard, and it automatically provides a user with a list of suggested components. These suggestions complete or ex- tend the electronic functionality of the inserted component to save the user's time and reduce circuit error. To demon- strate the effectiveness of autocomplete, we implemented our system on Fritzing, a popular open source breadboard circuit prototyping software, used by novice makers. Our autocomplete suggestions were implemented based upon schematics from datasheets for standard components, as well as how components are used together from over 4000 circuit projects from the Fritzing community. We report the results of a controlled study with 16 participants, evaluating the effectiveness of autocomplete in the creation of virtual breadboard circuits, and conclude by sharing insights and directions for future research.2019JLJo-Yu Lo et al.National Chiao Tung UniversityCircuit Making & Hardware PrototypingCHI
Tessutivo: Contextual Interactions on Interactive Fabrics with Inductive SensingWe present Tessutivo, a contact-based inductive sensing technique for contextual interactions on interactive fabrics. Our technique recognizes conductive objects (mainly metallic) that are commonly found in households and workplaces, such as keys, coins, and electronic devices. We built a prototype containing six by six spiral-shaped coils made of conductive thread, sewn onto a four-layer fabric structure. We carefully designed the coil shape parameters to maximize the sensitivity based on a new inductance approximation formula. Through a ten- participant study, we evaluated the performance of our proposed sensing technique across 27 common objects. We yielded 93.9% real-time accuracy for object recognition. We conclude by presenting several applications to demonstrate the unique interactions enabled by our technique.2019JGJun Gong et al.Electronic Textiles (E-textiles)On-Skin Display & On-Skin InputUIST