EDBT 2026 Demo / reviewers in the wild / expert
Yuta Kazama
dblp:151/9750
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—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 |
Haptics and multimodal interaction · 77% Learning and educational technologies · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Haptics and multimodal interaction › tactile display
softness display |
0.2 | 1 | 2014 | Softness display by a multi-fingered haptic interface robot · ICRA 2014 |
Learning and educational technologies › medical training
medical training systems |
0.1 | 1 | 2014 | Softness display by a multi-fingered haptic interface robot · ICRA 2014 |
Methods — techniques the papers use, named apart from their topics
multi-fingered haptic interface · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Softness display by a multi-fingered haptic interface robotabstractWhen we touch a human body, the flesh yields to our touch and we feel a sensation of softness. In virtual training systems for medical procedures such as palpation, the display of softness at the fingertips is essential. This paper proposes a softness-display device using a flexible sheet, and we present the concept of softness display at multiple fingers by combining the developed softness-display device and a multi-fingered haptic interface robot consisting of a five-fingered hand and an arm. Further, we carried out several experiments, the results of which show the validity of the proposed system and its great potential. Takahiro Endo, Satoshi Tanimura, Yuta Kazama, Haruhisa Kawasaki |
ICRA | 3 |