Basic research on an auxiliary system of Sit-to-Stand motion using lower limb EMG based on fast statisticl learning
| Project/Area Number |
25350669
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Rehabilitation science/Welfare engineering
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| Research Institution | The University of Tokushima |
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Principal Investigator |
Fukumi Minoru 徳島大学, ソシオテクノサイエンス研究部, 教授 (80199265)
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| Project Period (FY) |
2013-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2015: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2014: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2013: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
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| Keywords | 筋肉電位 / Simple-PCA / Simple-FLDA / 統計学習 / 足首動作 |
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| Outline of Final Research Achievements |
In this research, a system to recognize ankle motions and to model a Sit-to-Stand motion using ankle EMG signals is developed for power-support devices. First, three motions of ankle, neutral, doesiflexion and plantar flexion using ankle EMG signals are recognized and 95% high accuracy is obtained for on-line experiments. Next, the Sit-to-Stand motion including three motions of ankle is recognized. The Sit-to-Stand motion is then divided into three motions. As a result, 62% accuracy is obtained and it is worse than that of three ankle motions. And also data distribution analysis in eigenspace showed that EMG data of Sit-to-Stand motion and that of three ankle motions measured at ankle are different. In the future, accuracy improvement including a normalization method for ankle EMG data for the Sit-to-Stand motion is needed.
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Report
(4 results)
Research Products
(5 results)
