Robust finger motion classification using frequency characteristics of surface electromyogram signals
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| Format: | Working Paper |
| Language: | en |
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Institute of Electrical and Electronics Engineers (IEEE)
2012
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| Online Access: | http://dspace.unimap.edu.my/123456789/21421 |
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| _version_ | 1837049742766374912 |
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| author | Ishikawa, Keisuke Akita, Junichi Toda, Masashi Kondo, Kazuaki Sakurazawa, Shigeru Nakamura, Yuichi |
| author2 | g2110005@fun.ac.jp |
| author_facet | g2110005@fun.ac.jp Ishikawa, Keisuke Akita, Junichi Toda, Masashi Kondo, Kazuaki Sakurazawa, Shigeru Nakamura, Yuichi |
| author_sort | Ishikawa, Keisuke |
| building | UniMAP Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaysia Perlis |
| content_source | UniMAP Library Digital Repository |
| continent | Asia |
| country | Malaysia |
| description | Link to publisher's homepage at http://ieeexplore.ieee.org/ |
| format | Working Paper |
| id | my.unimap-21421 |
| institution | Universiti Malaysia Perlis |
| language | en |
| publishDate | 2012 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | my.unimap-214212012-10-18T08:33:44Z Robust finger motion classification using frequency characteristics of surface electromyogram signals Ishikawa, Keisuke Akita, Junichi Toda, Masashi Kondo, Kazuaki Sakurazawa, Shigeru Nakamura, Yuichi 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 Surface-Electromyogram Signals (EMG) Finger motion classification Frequency characteristics Tension estimate Link to publisher's homepage at http://ieeexplore.ieee.org/ 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. 2012-10-18T08:33:43Z 2012-10-18T08:33:43Z 2012-02-27 Working Paper p. 362-367 978-145771989-9 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6179039 http://dspace.unimap.edu.my/123456789/21421 en Proceedings of the International Conference on Biomedical Engineering (ICoBE 2012) Institute of Electrical and Electronics Engineers (IEEE) |
| spellingShingle | Surface-Electromyogram Signals (EMG) Finger motion classification Frequency characteristics Tension estimate Ishikawa, Keisuke Akita, Junichi Toda, Masashi Kondo, Kazuaki Sakurazawa, Shigeru Nakamura, Yuichi Robust finger motion classification using frequency characteristics of surface electromyogram signals |
| title | Robust finger motion classification using frequency characteristics of surface electromyogram signals |
| title_full | Robust finger motion classification using frequency characteristics of surface electromyogram signals |
| title_fullStr | Robust finger motion classification using frequency characteristics of surface electromyogram signals |
| title_full_unstemmed | Robust finger motion classification using frequency characteristics of surface electromyogram signals |
| title_short | Robust finger motion classification using frequency characteristics of surface electromyogram signals |
| title_sort | robust finger motion classification using frequency characteristics of surface electromyogram signals |
| topic | Surface-Electromyogram Signals (EMG) Finger motion classification Frequency characteristics Tension estimate |
| url | http://dspace.unimap.edu.my/123456789/21421 |
| url_provider | http://dspace.unimap.edu.my/ |