Takefumi Yamaguchi

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1ranked-venue papers

0as first author

0since 2021 · last 2005

—ORCID · unresolved

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

Accessibility and assistive technology · 46% Human-robot interaction · 46% Wearable and physiological sensing · 7%

Topics — the 5 heaviest of 5, each with the papers that count most for it

Topic	Weight	Papers	Last	Evidence papers
Accessibility and assistive technology assistive technology	0.1	1	2005	Adaptation Strategy for the 3DOF Exoskeleton for Upper-Limb Motion Assist · ICRA 2005
Human-robot interaction › human-in-the-loop control electromyography-based control	0.1	1	2005	Adaptation Strategy for the 3DOF Exoskeleton for Upper-Limb Motion Assist · ICRA 2005
Human-robot interaction › wearable robot exoskeleton	0.1	1	2005	Adaptation Strategy for the 3DOF Exoskeleton for Upper-Limb Motion Assist · ICRA 2005
Accessibility and assistive technology › assistive technology upper-limb motion assist	0.1	1	2005	Adaptation Strategy for the 3DOF Exoskeleton for Upper-Limb Motion Assist · ICRA 2005
Wearable and physiological sensing electromyography	0.0	1	2005	Adaptation Strategy for the 3DOF Exoskeleton for Upper-Limb Motion Assist · ICRA 2005

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

electromyography · 0.1

Year	Publication	Venue	Position
2005	Adaptation Strategy for the 3DOF Exoskeleton for Upper-Limb Motion Assist abstract Exoskeletons are expected to be used as wearable haptic devices and power assist robot systems. We have been studying exoskeletons to assist the human motion in daily activity and rehabilitation. The EMG (electromyogram), which directly reflects the human motion intention, has been used to control the exoskeleton without any special control equipment. This paper presents a strategy that realizes the effective adaptation of the EMG-based exoskeleton controller (i.e., robot-human interface) to any persons. Kazuo Kiguchi, Takefumi Yamaguchi	ICRA	3