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Soichiro Matsushita

dblp:47/6508 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2019
0009-0007-9424-2877ORCID · reported

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

Human-computer interaction and ubiquitous computing · 1 · 1 first-author

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%
Computer graphics and multimedia
1 paper
Audio and music processing · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wearable and physiological sensing › motion sensing
motion tracking
0.412019
A wrist-worn motion evaluation system for fast and powerful down picking of heavy metal guitar · UbiComp 2019
Audio and music processing › music analysis
music performance analysis
0.112019
A wrist-worn motion evaluation system for fast and powerful down picking of heavy metal guitar · UbiComp 2019

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

inertial motion tracking · 0.8
YearPublicationVenuePosition
2019 A wrist-worn motion evaluation system for fast and powerful down picking of heavy metal guitar
abstract
A fast and powerful down picking skill of rhythm guitar is crucial for heavy metal songs. At more than 400 beats per minute, which is a typical starting point for heavy metal songs, most players feel hard to keep the picking rhythm. In this paper, we propose a wrist-worn inertial motion tracking device for analyzing the guitar picking motion. A population test showed that a wrist twist angular velocity signal would give sufficient information on the picking timing to evaluate the accuracy of rhythm. It was also found that the power of sound had a strong correlation with the wrist twist angle and the upward linear acceleration signals. We developed a picking evaluation system by using characteristic motion parameters that informs the player of the speed, power, and smoothness of the picking motion. As a result, five out of eight beginners to play heavy metal guitar reached the speed of 400 beats per minute in a short training period.
Soichiro Matsushita
UbiComp1