Demo Data from SIGIR 2026 / reviewers in the wild / expert
Henry Tonoyan
dblp:203/5019
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Wearable and physiological sensing · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wearable and physiological sensing › flexible electronics
soft sensor fabrication |
0.3 | 1 | 2017 | Fabric sensory sleeves for soft robot state estimation · ICRA 2017 |
Methods — techniques the papers use, named apart from their topics
strain sensing · 0.3capacitive sensing · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Fabric sensory sleeves for soft robot state estimationabstractIn this paper, we describe the fabrication and testing of a stretchable fabric sleeve with embedded elastic strain sensors for state reconstruction of a soft robotic joint. The strain sensors are capacitive and composed of graphite-based conductive composite electrodes and a silicone elastomer dielectric. The sensors are screenprinted directly into the fabric sleeve, which contrasts the approach of pre-fabricating sensors and subsequently attaching them to a host. We demonstrate the capabilities of the sensor-embedded fabric sleeve by determining the joint angle and end effector position of a soft pneumatic joint with similar accuracy to a traditional IMU. Furthermore, we show that the sensory sleeve is capable of capturing more complex material states, such as fabric buckling and non-constant curvatures along linkages and joints. Michelle C. Yuen, Henry Tonoyan, Edward L. White, Maria J. Telleria, Rebecca Kramer-Bottiglio |
ICRA | 2 |