Hand motion identification using independent component analysis of data glove and multichannel surface EMG

Pei Jarn Chen, Ming Wen Chang, Yi Chun Du

研究成果: Conference contribution

摘要

This study presents an approach to identify hand motions using muscle activity separated from multichannel surface electromyogram (SEMG) and the information of data glove. There are nigh features included six features are extracted from each SEMG channel, and three features are computed from five bend sensors in the data glove. Independent Component Analysis (ICA) was used to examine its effect on independent component extraction and features reduction in this study. The results demonstrate that ICA can effectively reduce the amount of required computation data with the price of reduced identification rates. The results also indicate that the proposed method provides high accuracy (>90%) and fast processing time that is achieved to the performance of real-time system.

原文English
主出版物標題Innovation in Design, Communication and Engineering - Proceedings of the 3rd International Conference on Innovation, Communication and Engineering, ICICE 2014
編輯Teen-Hang Meen, Stephen D. Prior, Artde Donald Kin-Tak Lam
發行者CRC Press/Balkema
頁面159-162
頁數4
ISBN(列印)9781138027527
DOIs
出版狀態Published - 2015
事件3rd International Conference on Innovation, Communication and Engineering, ICICE 2014 - Guiyang, Guizhou, China
持續時間: 2014 十月 172014 十月 22

出版系列

名字Innovation in Design, Communication and Engineering - Proceedings of the 3rd International Conference on Innovation, Communication and Engineering, ICICE 2014

Other

Other3rd International Conference on Innovation, Communication and Engineering, ICICE 2014
國家/地區China
城市Guiyang, Guizhou
期間14-10-1714-10-22

All Science Journal Classification (ASJC) codes

  • 電腦網路與通信
  • 資訊系統

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