arXiv subjects

Devin Murphy

Publications and source records attributed to Devin Murphy.

4 recordsLinked to original sources

arXiv2026

KnitID: Machine-Knitted RFID Antennas for Battery-Free Authentication, Localization and Interaction

Battery-free RFID systems offer a scalable and maintenance-free approach to interaction. We present KnitID, a machine-knitted textile RFID antenna design that enables on-body authentication, localization, and interaction. Unlike prior antenna designs, KnitID achieves a compact antenna form factor (60mm by 8mm) by integrating magnet wire into the unique loop-over-loop structure of machine knitting. This structure reduces the size of conventional loop antennas by around 90\%, while also providing 30\% longer sensing ranges than standard dipole designs with similar size on the human body. The compact form factor creates new opportunities to embed multiple RFID tags across the human body, enriching backscatter signals and supporting a broader range of battery-free on-body interactions. To demonstrate this capability, we build an interactive sleeve to support wearer authentication, spatial localization, and interaction detection. Through technical evaluations, we show the feasibility of KnitID to provide diverse and battery-free interactions on knitted user interfaces.

cs.HC↗

arXiv2025

OPENTOUCH: Bringing Full-Hand Touch to Real-World Interaction

The human hand is our primary interface to the physical world, yet egocentric perception rarely knows when, where, or how forcefully it makes contact. Robust wearable tactile sensors are scarce, and no existing in-the-wild datasets align first-person video with full-hand touch. To bridge the gap between visual perception and physical interaction, we present OpenTouch, the first in-the-wild egocentric full-hand tactile dataset, containing 5.1 hours of synchronized video-touch-pose data and 2,900 curated clips with detailed text annotations. Using OpenTouch, we introduce retrieval and classification benchmarks that probe how touch grounds perception and action. We show that tactile signals provide a compact yet powerful cue for grasp understanding, strengthen cross-modal alignment, and can be reliably retrieved from in-the-wild video queries. By releasing this annotated vision-touch-pose dataset and benchmark, we aim to advance multimodal egocentric perception, embodied learning, and contact-rich robotic manipulation.

cs.CV↗

arXiv2025

Fits like a Flex-Glove: Automatic Design of Personalized FPCB-Based Tactile Sensing Gloves

Resistive tactile sensing gloves have captured the interest of researchers spanning diverse domains, such as robotics, healthcare, and human-computer interaction. However, existing fabrication methods often require labor-intensive assembly or costly equipment, limiting accessibility. Leveraging flexible printed circuit board (FPCB) technology, we present an automated pipeline for generating resistive tactile sensing glove design files solely from a simple hand photo on legal-size paper, which can be readily supplied to commercial board houses for manufacturing. Our method enables cost-effective, accessible production at under \$130 per glove with sensor assembly times under 15 minutes. Sensor performance was characterized under varying pressure loads, and a preliminary user evaluation showcases four unique automatically manufactured designs, evaluated for their reliability and comfort.

cs.HC↗

arXiv2024

WiReSens Toolkit: An Open-source Platform towards Accessible Wireless Tactile Sensing

Past research has widely explored the design and fabrication of resistive matrix-based tactile sensors as a means of creating touch-sensitive devices. However, developing portable, adaptive, and long-lasting tactile sensing systems that incorporate these sensors remains challenging for individuals having limited prior experience with them. To address this, we developed the WiReSens Toolkit, an open-source platform for accessible wireless tactile sensing. Central to our approach is adaptive hardware for interfacing with resistive sensors and a web-based GUI that mediates access to complex functionalities for developing scalable tactile sensing systems, including 1) multi-device programming and wireless visualization across three distinct communication protocols 2) autocalibration methods for adaptive sensitivity and 3) intermittent data transmission for low-power operation. We validated the toolkit's usability through a user study with 11 novice participants, who, on average, successfully configured a tactile sensor with over 95\% accuracy in under five minutes, calibrated sensors 10x faster than baseline methods, and demonstrated enhanced tactile data sense-making.

cs.HC↗