2014年6月
EMG-Force-Sensorless Power Assist System Control based on Multi-Class Support Vector Machine
11th IEEE International Conference on Control and Automation (ICCA)
- ,
- ,
- ,
- 開始ページ
- 284
- 終了ページ
- 289
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1109/ICCA.2014.6870933
- 出版者・発行元
- IEEE
This paper aims to describe a framework implementing Multi-Class Support Vector Machine (MCSVM)based motion intention recognition. To this end, we primarily constructed a wearable exoskeleton robot of lower body (TTI-Exo) which is employed as the experimentation platform to test the proposed method of motion intention recognition based on MCSVM and the assist effectiveness as well. Experiments of stand-to-sit and sit-to-stand movements were carried out to test the MCSVM method and TTI-Exo's motion assist. Having disclosed prototype development, experimental results are presented. We verified that our proposed method based on MCSVM obtained a better recognition accuracy than a conventional method based on threshold values. Muscle activities when subjects wearing TTI-Exo were much smaller than when subjects not wearing the exoskeleton, thus implying the assist efficacy of our power assist system.
- リンク情報
- ID情報
-
- DOI : 10.1109/ICCA.2014.6870933
- ISSN : 1948-3449
- Web of Science ID : WOS:000346501200048