Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Yushi Sato

dblp:247/3832 · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0003-1186-0308ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 2 · 1 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 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
2 papers
Human-robot interaction · 46% Haptics and multimodal interaction · 40% Health and well-being technologies · 14%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction › affective interaction
affective touch
0.612022
Hugmon: Exploration of Affective Movements for Hug Interaction using Tensegrity Robot · HRI 2022
Haptics and multimodal interaction › multimodal feedback
visuo-haptic feedback
0.412019
fARFEEL: Providing Haptic Sensation of Touched Objects Using Visuo-Haptic Feedback · VR 2019
Health and well-being technologies › mental health
mental healthcare
0.212022
Hugmon: Exploration of Affective Movements for Hug Interaction using Tensegrity Robot · HRI 2022
Haptics and multimodal interaction › haptic feedback
tactile feedback
0.112019
fARFEEL: Providing Haptic Sensation of Touched Objects Using Visuo-Haptic Feedback · VR 2019

Methods — techniques the papers use, named apart from their topics

user study · 0.6tensegrity robot · 0.6visuo-haptic feedback · 0.4projected virtual hand · 0.4
YearPublicationVenuePosition
2022 Hugmon: Exploration of Affective Movements for Hug Interaction using Tensegrity Robot
abstract
Since ancient times, a hug has been one of the most basic ways to express emotions and has played an important role in building relationships between people. On the other hand, social robots that are designed to provide mental health care to patients have been attracting great attention, and hugging between humans and robots is becoming more and more popular. In this study, we propose a huggable robot that allows intimate interactions between humans and robots. Our robot is based on a tensegrity structure, which is composed of rigid elements connected by springs, and the structure allows the robot to flexibly respond to external force from a hugging interaction, and express various emotions through its movements. In addition, we conducted user experiments and explored an interaction design for the affective movement of the proposed robot. Through the experiments, we confirm that a robot with a tensegrity structure can be used for a hug interaction and it has a large possibility for emotional interaction.
Naoya Yoshimura, Yushi Sato, Yuta Kageyama, Jun Murao, Satoshi Yagi, Parinya Punpongsanon
HRI2
2019 fARFEEL: Providing Haptic Sensation of Touched Objects Using Visuo-Haptic Feedback
abstract
We present fARFEEL, a remote communication system that provides visuo-haptic feedback allows a local user to feel touching distant objects. The system allows the local and remote users to communicate by using the projected virtual hand (VH) for the agency of his/her own hands. The necessary haptic information is provided to the non-manipulating hand of the local user that does not bother the manipulation of the projected VH. We also introduce the possible visual stimulus that could potentially provide the sense of the body ownership over the projected VH.
Naruki Tanabe, Yushi Sato, Kohei Morita, Parinya Punpongsanon, Haruka Matsukura, Michiya Inagaki, Daisuke Iwai, Yuichi Fujino, Kosuke Sato
VR2