EFFECT OF SURFACE ELECTRODE ORIENTATION ON INDEPENDENT COMPONENT ANALYSIS FOR FEATURE EXTRACTION OF SURFACE MOTOR UNIT ACTION POTENTIAL

被引：0

作者：

Akazawa, Jun ^{[1
]}

Ikeuchi, Takaharu ^{[1
]}

Okamoto, Takemasa ^{[1
]}

Okuno, Ryuhei ^{[2
]}

Yoshida, Masaki ^{[3
]}

Sato, Tetsuo ^{[4
]}

Minato, Kotaro ^{[4
]}

机构：

[1] Meiji Univ Integrat Med, Sch Hlth Sci & Med Care, Hiyoshi Cho, Nantan, Kyoto 6290392, Japan

[2] Setsunan Univ, Dept Elect & Elect Engn, Neyagawa, Osaka 5728508, Japan

[3] Osaka Electrocommun Univ, Dept Biomed Engn, Shijonawate, Osaka 570063, Japan

[4] Nara Inst Sci & Technol, Grad Sch Informat Sci, Ikom, Nara 6300192, Japan

来源：

BIOSIGNALS 2009: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING | 2009年

关键词：

Electromyogram; Motor Unit; Model; Independent Component Analysis;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Recently, application of Independent Component Analysis (ICA) has been reported for effective decomposition of surface electromyogram (SEMG) signals into a train of surface motor unit action potentials (SMUAPs) of a single motor unit (MU). Results of ICA were not always sufficient as the feature extraction of SWAP at first dorsal interosseous muscle (FDI). The purpose of this study is to propose an effective method for feature extraction of SMUAP by simulation study of focusing on the effects of electrode orientation. SEMG signals were created with the model and application of ICA was applied to the signals. The present study showed that the useful and actual method of ICA application was to repeat measurement of SEMG signals with varying the electrode orientation, and then to select the better signals for the feature extraction by executing ICA algorithm.

引用

页码：421 / +

页数：3

共 11 条

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