Demo Data from SIGIR 2026 / reviewers in the wild / expert
Jiseung Cho
dblp:181/4247
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2016
—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 › motion sensing
motion monitoring |
0.1 | 1 | 2016 | Printable skin adhesive stretch sensor for measuring multi-axis human joint angles · ICRA 2016 |
Methods — techniques the papers use, named apart from their topics
geometric calibration · 0.2carbon nanotube composite · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Printable skin adhesive stretch sensor for measuring multi-axis human joint anglesabstractThis paper presents a printable skin adhesive stretch sensor to estimate rotation angles of multi-axis joint for biomedical engineering applications, such as gait analysis, gesture recognition, and motion monitoring. Silicone rubber mixed with multiwall carbon nanotube composites were fabricated to make a highly stretchable (up to 120%) strain sensors. Embedding liquid state composites to the fabric leaded to enhance the adhesive force between the composites and fabric. The skin adhesive sensor system could be used to estimate rotation angles of the multi-axis joints while providing comfortable physical interfaces. To reduce misalignment to the axis of rotation, a calibration method was formulated based on geometrical relationship between the sensor axes and the joint angle. In order to validate the estimation performance of the sensor in multi-axis joint, shoulder flexion/extension and abduction/adduction angles were estimated. The results showed the system could estimate the rotation angles of the shoulder enough to identify motion intentions of the user. In the future, the proposed system can be applied to the motion monitoring system by direct attachment to skin without discomfort to the user in daily life. Hyosang Lee, Jiseung Cho, Jung Kim |
ICRA | 2 |