| Project/Area Number |
25540116
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Intelligent robotics
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
OKADA Masafumi 東京工業大学, 理工学研究科, 准教授 (60323523)
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| Project Period (FY) |
2013-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2014: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2013: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | 胸骨圧迫 / 運動最適化 / データフィルタ / 学習の力学モデル / 強調姿勢 / 人の力学モデル |
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| Outline of Final Research Achievements |
The chest compression is one of the most important actions for first-aid cardiopulmonary resuscitation. Because it requires large torque/force to be generated, the performers have to take an energy saving position and motion until advanced life support providers take over. The energy saving motion strictly depends on the body weight and height of the performers. In this research, the chest compression is optimized from kinematic and dynamic point of view. By using Pseudo-differential and zero-phase filter, the angular velocity and acceleration are derived from a motion capture data, and generative force is calculated by inverse dynamic computation. Based on an evaluation function and constraints, the chest compression is optimized kinematically, dynamically and temporally. Moreover, for the chest compression of a child with light weight, a motion aid is optimized. The effectiveness of the proposed method is evaluated based on a physical load of the performers by measuring heart rate.
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