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
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
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
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
Instrumenting and Analyzing Fabrication Activities, Users, and ExpertiseThe recent proliferation of fabrication and making activities has introduced a large number of users to a variety of tools and equipment. Monitored, reactive and adaptive fabrication spaces are needed to provide personalized information, feedback and assistance to users. This paper explores the sensorization of making and fabrication activities, where the environment, tools, and users were considered to be separate entities that could be instrumented for data collection. From this exploration, we present the design of a modular system that can capture data from the varied sensors and infer contextual information. Using this system, we collected data from fourteen participants with varying levels of expertise as they performed seven representative making tasks. From the collected data, we predict which activities are being performed, which users are performing the activities, and what expertise the users have. We present several use cases of this contextual information for future interactive fabrication spaces.2019JGJun Gong et al.Autodesk Research & Dartmouth CollegeDesktop 3D Printing & Personal FabricationCircuit Making & Hardware PrototypingComputational Methods in HCICHI
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
Proxino: Enabling Prototyping of Virtual Circuits With Physical ProxiesWe propose blending the virtual and physical worlds for prototyping circuits using physical proxies. With physical proxies, real-world components (e.g. a motor, or light sensor) can be used with a virtual counterpart for a circuit designed in software. We demonstrate this concept in Proxino, and elucidate the new scenarios it enables for makers, such as remote collaboration with physically distributed electronics components. We compared our hybrid system and its output with designs of real circuits to determine the difference through a system evaluation and observed minimal differences. We then present the results of an informal study with 9 users, where we gathered feedback on the effectiveness of our system in different working conditions (with a desktop, using a mobile, and with a remote collaborator). We conclude by sharing our lessons learned from our system and discuss directions for future research that blend physical and virtual prototyping for electronic circuits.2019TWTe-Yen Wu et al.Desktop 3D Printing & Personal FabricationCircuit Making & Hardware PrototypingUIST
TipText: Eyes-Free Text Entry on a Fingertip KeyboardIn this paper, we propose and investigate a new text entry technique using micro thumb-tip gestures. Our technique features a miniature QWERTY keyboard residing invisibly on the first segment of the user’s index finger. Text entry can be carried out using the thumb-tip to tap the tip of the index finger. The keyboard layout was optimized for eyes-free input by utilizing a spatial model reflecting the users’ natural spatial awareness of key locations on the index finger. We present our approach of designing and optimizing the keyboard layout through a series of user studies and computer simulated text entry tests over 1,146,484 possibilities in the design space. The outcome is a 2×3 grid with the letters highly confining to the alphabetic and spatial arrangement of QWERTY. Our one-day user evaluation showed that participants achieved an average text entry speed of 11.9 WPM and were able to type as fast as 13.3 WPM towards the end of the experiment.2019ZXZheer Xu et al.Foot & Wrist InteractionMotor Impairment Assistive Input TechnologiesUIST
WrisText: One-handed Text Entry on Smartwatch using Wrist GesturesWe present WrisText - a one-handed text entry technique for smartwatches using the joystick-like motion of the wrist. A user enters text by whirling the wrist of the watch hand, towards six directions which each represent a key in a circular keyboard, and where the letters are distributed in an alphabetical order. The design of WrisText was an iterative process, where we first conducted a study to investigate optimal key size, and found that keys needed to be 55º or wider to achieve over 90% striking accuracy. We then computed an optimal keyboard layout, considering a joint optimization problem of striking accuracy, striking comfort, word disambiguation. We evaluated the performance of WrisText through a five-day study with 10 participants in two text entry scenarios: hand-up and hand-down. On average, participants achieved a text entry speed of 9.9 WPM across all sessions, and were able to type as fast as 15.2 WPM by the end of the last day.2018JGJun Gong et al.Dartmouth CollegeFoot & Wrist InteractionCHI
Jetto: Using Lateral Force Feedback for Smartwatch InteractionsInteracting with media and games is a challenging user experience on smartwatches due to their small screens. We propose using lateral force feedback to enhance these experiences. When virtual objects on the smartwatch display visually collide or push the edge of the screen, we add haptic feedback so that the user also feels the impact. This addition creates the illusion of a virtual object that is physically hitting or pushing the smartwatch, from within the device itself. Using this approach, we extend virtual space and scenes into a 2D physical space. To create realistic lateral force feedback, we first examined the minimum change in force magnitude that is detectable by users in different directions and weight levels, finding an average JND of 49% across all tested conditions, with no significant effect of weight and force direction. We then developed a proof-of-concept hardware prototype called Jetto and demonstrated its unique capabilities through a set of impact-enhanced videos and games. Our preliminary user evaluations indicated the concept was welcomed and is regarded as a worthwhile addition to smartwatch output and media experiences.2018JGJun Gong et al.Dartmouth CollegeForce Feedback & Pseudo-Haptic WeightSmartwatches & Fitness BandsCHI
Indutivo: Contact-Based, Object-Driven Interactions with Inductive SensingWe present Indutivo, a contact-based inductive sensing technique for contextual interactions. Our technique recognizes conductive objects (metallic primarily) that are commonly found in households and daily environments, as well as their individual movements when placed against the sensor. These movements include sliding, hinging, and rotation. We describe our sensing principle and how we designed the size, shape, and layout of our sensor coils to optimize sensitivity, sensing range, recognition and tracking accuracy. Through several studies, we also demonstrated the performance of our proposed sensing technique in environments with varying levels of noise and interference conditions. We conclude by presenting demo applications on a smartwatch, as well as insights and lessons we learned from our experience.2018JGJun Gong et al.Smartwatches & Fitness BandsUbiquitous ComputingUIST