Papers

FlowRing: Integrated Microgesture and Surface Interaction Ring for Versatile XR Input

As Extended Reality (XR) advances, a device has the potential to be used across contexts from immersive productivity at a desk to on-the-go, public scenarios. Existing input solutions lack the versatility to provide both high-throughput, mouse-grade input and subtle, ergonomic interaction. We introduce FlowRing, a novel ring-form device that combines microgestures with precise 2D mouse-like input on surfaces. FlowRing supports five microgestures for discreet interaction and 2D input for richer tasks, using an optical flow sensor, skin-contact microphone, and IMU at the base of the finger. In a study with 11 participants, FlowRing achieved 93.6% microgesture recognition accuracy across sessions and 85.2% across unseen users, rising to 90.1% with just four gesture set examples from a new user. A separate 2D Fitts’ law study demonstrated its effectiveness for continuous input on various surfaces. FlowRing emerges as a versatile, user-friendly solution for the future of interactive technology.

ECG Necklace: Low-power Wireless Necklace for Continuous ECG monitoring

Continuous, everyday ECG monitoring is essential for detecting transient heart conditions and enabling early intervention in cardiovascular diseases. However, current technologies, such as ECG Holter monitors and smartwatches, face challenges in balancing continuous monitoring with long-term wearability due to trade-offs in electrode placement. To address this, we present a novel ECG necklace that leverages its natural placement on the chest to provide continuous, clinically valuable ECG monitoring. Our design positions two electrodes on the left and right sides of the chest, approximating standard Lead I placement for accurate cardiac diagnostics. The necklace features an innovative skin moisture-enhanced electrode design for sustained comfort and integrates a compact 22-mm processing unit as the pendant, offering a 4-day battery life. In our studies, the ECG necklace demonstrated performance comparable to FDA-approved Holter monitors, with key features falling within a timing error range of 3.2–15.7 ms—well within acceptable limits. In our in-the-wild study, participants rated the necklace as highly comfortable and preferred it over traditional ECG monitors. As a widely accepted everyday accessory, the ECG necklace has the potential to seamlessly combine advanced functionality with daily wearability.

NightLight: Passively Mapping Nighttime Sidewalk Light Data for Improved Pedestrian Routing

Nighttime sidewalk illumination has a significant and unequal influence on where and whether pedestrians walk at night. Despite the importance of pedestrian lighting, there is currently no approach for measuring and communicating how humans experience nighttime sidewalk light levels at scale. We introduce NightLight, a new sensing approach that leverages the ubiquity of smartphones by re-appropriating the built-in light sensor ---traditionally used to adapt screen brightness---to sense pedestrian nighttime lighting conditions. We validated our technique through in-lab and street-based evaluations characterizing performance across phone orientation, phone model, and varying light levels demonstrating the ability to aggregate and map pedestrian-oriented light levels with unaltered smartphones. Additionally, to examine the impact of light level data on pedestrian route choice, we conducted a qualitative user study with 13 participants using a standard map vs. one with pedestrian lighting data from NightLight Our findings demonstrate that people changed their routes in preference of well-light routes during nighttime walking. Our work has implications for expanding personalized navigation and pedestrian route choice and passive urban sensing.

"A Tool for Freedom": Co-Designing Mobility Aid Improvements Using Personal Fabrication and Physical Interface Modules with Primarily Young Adults

Mobility aids (e.g., canes, crutches, and wheelchairs) are crucial for people with mobility disabilities; however, pervasive dissatisfaction with these aids keeps usage rates low. Through semi-structured interviews with 17 mobility aid users, mostly under the age of 30, we identified specific sources of dissatisfaction among younger users of mobility aids, uncovered community-based solutions for these dissatisfactions, and explored ways these younger users wanted to improve mobility aids. We found that users sought customizable, reconfigurable, multifunctional, and more aesthetically pleasing mobility aids. Participants' feedback guided our prototyping of tools/accessories, such as laser cut decorative skins, hot-swappable physical interface modules, and modular canes with custom 3D-printed handles. These prototypes were then the focus of additional co-design sessions where six returning participants offered suggestions for improvements and provided feedback on their usefulness and usability. Our findings highlight that many mobility aid users have the desire, ability, and need to customize and improve their aids in different ways compared to older adults. We propose various solutions and design guidelines to facilitate the modifications of mobility aids.

ProxiCycle : Passively Mapping Cyclist Safety Using Smart Handlebars for Near-Miss Detection

Active transportation is a valuable tool to prevent some of the most common causes of mortality worldwide, but is severely underutilized. The primary factors preventing cyclist adoption are safety concerns, specifically, the fear of collision from automobiles. One solution to address this concern is to direct cyclists to known safe routes to minimize risk and stress, thus making cycling more approachable. However, few localized safety priors are available, hindering safety based routing. Specifically, road user behavior is unknown. To address this issue, we develop a novel handlebar attachment to passively monitor the proximity of passing cars as a an indicator of cycling safety along historically traveled routes. We deploy this sensor with 15 experienced cyclists in a 2 month longitudinal study to source a citywide map of car passing distance. We then compare this signal to both historic collisions and perceived safety reported by experienced and inexperienced cyclists.

The EarSAVAS Dataset: Enabling Subject-Aware Vocal Activity Sensing on Earables

Zhang 等人构建 EarSAVAS 数据集，支持智能耳穿戴设备进行主体感知的语音活动检测，推动相关算法研究。

Thermal Earring: Low-power Wireless Earring for Longitudinal Earlobe Temperature Sensing

Xue 等人设计 Thermal Earring 智能耳饰，采用低功耗蓝牙实现长时间连续耳垂温度监测，为健康追踪提供可穿戴解决方案。

DeltaLCA: Comparative Life-Cycle Assessment for Electronics Design

WatchLink: Enhancing Smartwatches with Sensor Add-Ons via ECG Interface

We introduce a low-power communication method that lets smartwatches leverage existing electrocardiogram (ECG) hardware as a data communication interface. Our unique approach enables the connection of external, inexpensive, and low-power "add-on" sensors to the smartwatch, expanding its functionalities. These sensors cater to specialized user needs beyond those offered by pre-built sensor suites, at a fraction of the cost and power of traditional communication protocols, including Bluetooth Low Energy. To demonstrate the feasibility of our approach, we conduct a series of exploratory and evaluative tests to characterize the ECG interface as a communication channel on commercial smartwatches. We design a simple transmission scheme using commodity components, demonstrating cost and power benefits. Further, we build and test a suite of add-on sensors, including UV light, body temperature, buttons, and breath alcohol, all of which achieved testing objectives at low material cost and power usage. This research paves the way for personalized and user-centric wearables by offering a cost-effective solution to expand their functionalities.

LabelAId: Just-in-time AI Interventions for Improving Human Labeling Quality and Domain Knowledge in Crowdsourcing Systems

Crowdsourcing platforms have transformed distributed problem-solving, yet quality control remains a persistent challenge. Traditional quality control measures, such as prescreening workers and refining instructions, often focus solely on optimizing economic output. This paper explores just-in-time AI interventions to enhance both labeling quality and domain-specific knowledge among crowdworkers. We introduce LabelAId, an advanced inference model combining Programmatic Weak Supervision (PWS) with FT-Transformers to infer label correctness based on user behavior and domain knowledge. Our technical evaluation shows that our LabelAId pipeline consistently outperforms state-of-the-art ML baselines, improving mistake inference accuracy by 36.7% with 50 downstream samples. We then implemented LabelAId into Project Sidewalk, an open-source crowdsourcing platform for urban accessibility. A between-subjects study with 34 participants demonstrates that LabelAId significantly enhances label precision without compromising efficiency while also increasing labeler confidence. We discuss LabelAId's success factors, limitations, and its generalizability to other crowdsourced science domains.

Modeling the Trade-off of Privacy Preservation and Activity Recognition on Low-Resolution Images

A computer vision system using low-resolution image sensors can provide intelligent services (e.g., activity recognition) but preserve unnecessary visual privacy information from the hardware level. However, preserving visual privacy and enabling accurate machine recognition have adversarial needs on image resolution. Modeling the trade-off of privacy preservation and machine recognition performance can guide future privacy-preserving computer vision systems using low-resolution image sensors. In this paper, using the at-home activity of daily livings (ADLs) as the scenario, we first obtained the most important visual privacy features through a user survey. Then we quantified and analyzed the effects of image resolution on human and machine recognition performance in activity recognition and privacy awareness tasks. We also investigated how modern image super-resolution techniques influence these effects. Based on the results, we proposed a method for modeling the trade-off of privacy preservation and activity recognition on low-resolution images.

Z-Ring: Single-point Bio-impedance Sensing for Gesture, Touch, Object and User Recognition

We present Z-Ring, a wearable ring that enables gesture input, object detection, user identification, and interaction with passive user interface (UI) elements using a single sensing modality and a single point of instrumentation on the finger. Z-Ring uses active electrical field sensing to detect changes in the hand's electrical impedance caused by finger motions or contact with external surfaces. We develop a diverse set of interactions and evaluate them with 21 users. We demonstrate: (1) Single- and two-handed gesture recognition with up to 93\% accuracy (2) Tangible input with a set of passive touch UI elements, including buttons, a continuous 1D slider, and a continuous 2D trackpad with 91.8\% accuracy, <4.4 cm MAE, and <4.1cm MAE, respectively (3) Object recognition across six household objects with 94.5\% accuracy (4) User identification among 14 users with 99\% accuracy. Z-Ring's sensing methodology uses only a single co-located electrode pair for both receiving and sensing, lending itself well to future miniaturization for use in on-the-go scenarios.

Understanding People's Concerns and Attitudes Toward Smart Cities

Designing privacy-respecting and human-centric smart cities requires a careful investigation of people's attitudes and concerns toward city-wide data collection scenarios. To capture a holistic view, we carried out this investigation in two phases. We first surfaced people's understanding, concerns, and expectations toward smart city scenarios by conducting 21 semi-structured interviews with people in underserved communities. We complemented this in-depth qualitative study with a 348-participant online survey of the general population to quantify the significance of smart city factors (e.g., type of collected data) on attitudes and concerns. Depending on demographics, privacy and ethics were the two most common types of concerns among participants. We found the type of collected data to have the most and the retention time to have the least impact on participants' perceptions and concerns about smart cities. We highlight key takeaways and recommendations for city stakeholders to consider when designing inclusive and protective smart cities.

ARDW: An Augmented Reality Workbench for Printed Circuit Board Debugging

Debugging printed circuit boards (PCBs) can be a time-consuming process, requiring frequent context switching between PCB design files (schematic and layout) and the physical PCB. To assist electrical engineers in debugging PCBs, we present ARDW, an augmented reality workbench consisting of a monitor interface featuring PCB design files, a projector-augmented workspace for PCBs, tracked test probes for selection and measurement, and a connected test instrument. The system supports common debugging workflows for augmented visualization on the physical PCB as well as augmented interaction with the tracked probes. We quantitatively and qualitatively evaluate the system with 10 electrical engineers from industry and academia, finding that ARDW speeds up board navigation and provides engineers with greater confidence in debugging. We discuss practical design considerations and paths for improvement to future systems. A video demo of the system may be accessed here: https://youtu.be/RbENbf5WIfc.

MoveVR: Enabling Multiform Force Feedback in Virtual Reality using Household Cleaning Robot

Haptic feedback can significantly enhance the realism and immersiveness of virtual reality (VR) systems. In this paper, we propose MoveVR, a technique that enables realistic, multiform force feedback in VR leveraging commonplace cleaning robots. MoveVR can generate tension, resistance, impact and material rigidity force feedback with multiple levels of force intensity and directions. This is achieved by changing the robot's moving speed, rotation, position as well as the carried proxies. We demonstrated the feasibility and effectiveness of MoveVR through interactive VR gaming. In our quantitative and qualitative evaluation studies, participants found that MoveVR provides more realistic and enjoyable user experience when compared to commercially available haptic solutions such as vibrotactile haptic systems.