An Efficient Approach for Feature Selection of SEMG Signal

被引：0
|
作者：
Liang Qi [1 ]
Ye Ming [1 ]
Ma Wenjie [1 ]
机构：
[1] Hanzghou Dianzi Univ, Inst Intelligent Control & Robert Res, Hangzhou 310018, Zhejiang, Peoples R China
来源：
PROCEEDINGS OF THE 2008 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN, VOL 2 | 2008年
关键词：
D O I：
10.1109/ISCID.2008.171
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper introduces an approach to obtain the feature vectors of surface electromyography (sEMG) signal based on Hilbert Huang Transform (HHT). An adaptive segmentation method that could effectively select appropriate Intrinsic Mode Function (IMF) is proposed. With the features gathered by using the energy of one channel signal, we also provide an optimized strategy based on experiments and experiences to increase the recognition rate of hand-motion patterns. The results from SVM neural networks classifier are presented to support this approach.
引用
收藏
页码：134 / 137
页数：4
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