Speed Based Surface EMG Classification Using Fuzzy Logic for Prosthetic Hand Control

被引：0
|
作者：
Ahmad, S. A. [1 ]
Ishak, A. J. [1 ]
Ali, S. H. [2 ]
机构：
[1] Univ Putra Malaysia, Dept Elect & Elect Engn, Fac Engn, Serdang, Malaysia
[2] Univ Kebangsaan Malaysia, Fac Engn & Built Environm, Dept Elect Elect & Syst, Bangi 43600, Malaysia
来源：
5TH KUALA LUMPUR INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING 2011 (BIOMED 2011) | 2011年 / 35卷
关键词：
prosthesis control; electromyography; fuzzy logic; feature extraction; classification; APPROXIMATE ENTROPY;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
Electromyographic (EMG) signal is an established technique for the control of a prosthetic hand. In its simplest form, the signals allow for opening a hand and subsequent closing to grasp an object. An EMG control system consists of two main components: feature extraction and classification. Using the information from different speeds of contraction, this paper describes the classification stage of the signal in determining the final grip postures of the hand. Fuzzy logic (FL) system is used in classifying the final information and the results demonstrate the ability of the system to discriminate the output successfully.
引用
收藏
页码：121 / +
页数：2
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