ITM Web Conf.
Volume 7, 20163rd Annual International Conference on Information Technology and Applications (ITA 2016)
|Number of page(s)||7|
|Section||Session 9: Computer Science and its Applications|
|Published online||21 November 2016|
Grasping Pattern Recognition and Grasping Force Estimation For Prosthetic Hands
1 School of Mechanical and Electrical Engineering, Central South University, 410083, Changsha, Hunan, China
2 State Key Laboratory of High-Performance Complex Manufacturing, Central South University, 410083, Changsha, Hunan, China
a Corresponding author: firstname.lastname@example.org
Human’s movement can be decoded by surface electromyography (EMG), and the prosthetic hand can be controlled freely through EMG signal. This paper proposes a grasping pattern and force synchronized decoding method for prosthetic hands. Considering pattern recognition and force estimation simultaneously, this paper analyzes whether different muscle contraction levels affect pattern recognition and whether different grasping modes have impact on force estimation, then proposes two schemes to complete EMG simultaneously decoding. Experiments compare the accuracy of the two methods. The results show that there is no much difference between two methods in force estimation, the former’s accuracy of pattern recognition is a little higher than the latter.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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