2013 Fiscal Year Final Research Report
Research on New Interface Using Wrist and Ankle EMG
| Project/Area Number |
22500202
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Sensitivity informatics/Soft computing
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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) |
2010-10-20 – 2014-03-31
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| Keywords | 筋肉電位（EMG) / 統計学習法 / Simple-FLDA |
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| Research Abstract |
In this research, first, a simple Kernel Discriminant Analysis (Simple-FLDA) for higher recognition performance by applying a kernel trick to the linear Simple-FLDA (Fisher Linear Discriminant Analysis) is developed. The Simple-FLDA algorithm is composed with simple calculations, but in recognition experiments using the UCI datasets as well as face image dataset; its features equal or surpass those of the Simple-FLDA algorithm.
Next, finger motions of the Janken "rock", "Scissors", "paper" and when not doing anything "neutral" were recognized by using wrist EMG signals. Off-line recognition and On-line recognition accuracies are 80% and 70%, respectively. Furthermore, three ankle motions were recognized by using ankle EMG signals. In this experiment, feature vectors are generated by On-line training using the Simple FLDA. Recognition accuracy is greater than 95%.
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Research Products
(14 results)
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[Presentation] Classification of Ankle Motions by EMG2012
Author(s)
Yusuke Yamamura, Yohei Takeuchi, Momoyo Ito, Koji Kashihara and Minoru Fukumi
Organizer
Proceeding of 2012 International Workshop on Nonlinear Circuits, Communication and Signal Processing NCSP'12
Place of Presentation
Waikiki Beach Marriott Resort and Spa Hotel(Honolulu, USA), (pp.285-288)
Year and Date
2012-03-02
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