Contrivance of new motor-skill learning system utilizing virtual-reality technology.
| Project/Area Number |
13358001
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 展開研究 |
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| Research Field |
体育学
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| Research Institution | The University of Tokyo |
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Principal Investigator |
OHTSUKI Tatsuyuki The University of Tokyo, Graduate School of Arts and Sciences, Professor, 大学院・総合文化研究科, 教授 (30093553)
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| Co-Investigator(Kenkyū-buntansha) |
UEDA Minoru The University of Aizu, School of Computer Science and Engineering, Assistant Professor, コンピュータ理工学部, 講師 (10254062)
KUDO Kazutoshi The University of Tokyo, Graduate School of Arts and Sciences, Research Associate, 大学院・総合文化研究科, 助手 (30302813)
品川 嘉久 東京大学, 大学院・情報理工学系研究科, 講師 (00226135)
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| Project Period (FY) |
2001 – 2003
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| Project Status |
Completed (Fiscal Year 2003)
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| Budget Amount *help |
¥29,900,000 (Direct Cost: ¥23,000,000、Indirect Cost: ¥6,900,000)
Fiscal Year 2003: ¥8,450,000 (Direct Cost: ¥6,500,000、Indirect Cost: ¥1,950,000)
Fiscal Year 2002: ¥10,530,000 (Direct Cost: ¥8,100,000、Indirect Cost: ¥2,430,000)
Fiscal Year 2001: ¥10,920,000 (Direct Cost: ¥8,400,000、Indirect Cost: ¥2,520,000)
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| Keywords | Virtual-reality / Computer Graphics / EMG / motor learning / motor skill / target-catching / sports / practice / スキル / 投球動作 / 筋電図 / スポーツ動作 / ビデオ解析 / トルク / 筋活動 / 時系列的筋活動 / 動作分析 / 3次元画像解析 / interactionトルク / muscleトルク |
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| Research Abstract |
This study was designed to contrive a new motor-skill practice tool that can be used regardless of the weather conditions and the size of practice areas with less anxiety about the injuries, utilizing virtual-reality technology. The model task employed in this study was target-catching tasks in which players should deal swiftly with rapidly changing situations in wide areas.
The study consisted of the following three steps.
1.Acquisition of the basic kinematic, kinetic and electromyographic data of the whole-body sport activities such as an overarm baseball throwing and various stroking movements of the badminton.
2.Contriving virtual-ball catching system using a virtual prehension glove and a CG animation of the ball and the baseball pitcher on a computer display.
3.Making a CG animation of the whole-body skeleton with skeletal muscles. The movements of the skeleton were realized by installing actually recorded learner's movement parameters. The intensity of the muscle activity was expressed by changing color density. This CG can be used as a visual feedback of a learner and can be applied to all human movements including sport activities as a tool of testing motor skill.
We will continue this study to make CG animations of many more sports activities, to test its applicability to the real skill practice, in order to complete an inexpensive and versatile motor-skill learning system that can be applied to all kinds of human movements.
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Report
(4 results)
Research Products
(6 results)
