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http://hdl.handle.net/123456789/21421
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| Title: | Robust finger motion classification using frequency characteristics of surface electromyogram signals |
| Authors: | Ishikawa, Keisuke
Akita, Junichi
Toda, Masashi
Kondo, Kazuaki
Sakurazawa, Shigeru
Nakamura, Yuichi |
| E-mail: | g2110005@fun.ac.jp
akita@is.t.kanazawau.ac.jp
toda@fun.ac.jp
kondo@media.kyotou.ac.jp
sakura@fun.ac.jp
yuichi@ccm.media.kyotou.ac.jp |
| Keywords: | Surface-Electromyogram Signals (EMG)
Finger motion classification
Frequency characteristics
Tension estimate |
| Issue Date: | 27-Feb-2012 |
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
| Citation: | p. 362-367 |
| Series/Report no.: | Proceedings of the International Conference on Biomedical Engineering (ICoBE 2012) |
| Abstract: | Finger motion classification using surface
electromyogram (EMG) signals is currently being applied to myoelectric prosthetic hands with methods of pattern classification. It can be used to classify motion with great
accuracy under ideal circumstances. However, the precision of classification falling to change the quantity of EMG feature with
muscle fatigue has been a problem. We addressed this problem in this study, which was aimed at robustly classifying finger motion against changes in EMG features with muscle fatigue. We tested the changes in EMG features before and after muscle fatigue and
propose a robust feature that uses a methods of estimating tension in finger motion by taking muscle fatigue into consideration. |
| Description: | Link to publisher's homepage at http://ieeexplore.ieee.org/ |
| URI: | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6179039
http://hdl.handle.net/123456789/21421 |
| ISBN: | 978-145771989-9 |
| Appears in Collections: | Conference Papers
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