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Shiina Takano

dblp:332/1419 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0000-0003-3795-6033ORCID · reported

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

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

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
Accessibility and assistive technology · 77% Games and playful interaction · 23%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Accessibility and assistive technology › software accessibility
game accessibility
1.012026
MYOLINK esports: Exploring EMG-based Control Interface through Muscle Activation and Inhibition to Enable Common Gameplay Mechanics among Players with and without Physical Disabilities · CHI 2026

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

user study · 1.0EMG sensing · 1.0
YearPublicationVenuePosition
2026 MYOLINK esports: Exploring EMG-based Control Interface through Muscle Activation and Inhibition to Enable Common Gameplay Mechanics among Players with and without Physical Disabilities
abstract
Esports have highlighted both their potential for social inclusion and the accessibility challenges faced by individuals with physical disabilities. This study introduces a novel paradigm for inclusive esports by shifting game control from traditional kinematic inputs to kinetic inputs. An EMG-based control interface enables gameplay through force regulation (e.g., muscle activation and inhibition). The aim is to explore how this interface enables common gameplay mechanics among players with and without physical disabilities. User Study 1 involved 20 able-bodied participants performing competitive esports tasks to examine how EMG-based control accuracy is influenced by movement range, such as wrist and elbow motion. User Study 2 extended the investigation to eight participants with physical disabilities to compare control accuracy between disabled and able-bodied users. The findings suggest that the interface enables common gameplay mechanics for individuals who can separately control activation and inhibition of each muscle corresponding to each EMG sensor via calibration adjustment but disability-related involuntary muscle activity and unintended co-contraction remains a major challenge for the interface.
Masato Shindo, Shiina Takano, Shuto Sako, Akihiro Miyata, Ryosuke Aoki
CHI2