Muscle fatigue compensation of the electromyography signal for elbow joint angle estimation using adaptive feature

被引：26
|
作者：
Triwiyanto, Triwiyanto [1 ,3 ]
Wahyunggoro, Oyas [1 ]
Nugroho, H. A. [1 ]
Herianto, Herianto [2 ]
机构：
[1] Univ Gadjah Mada, Fac Engn, Dept Elect Engn & Informat Technol, Grafika 2, Yogyakarta, Indonesia
[2] Univ Gadjah Made, Fac Engn, Dept Mech & Ind Engn, Grafika 2, Yogyakarta, Indonesia
[3] Minist Hlth Indonesia, Politekn Kesehatan Surabaya, Dept Electromed Engn, Pucang Jajar Timur 10, Surabaya, Indonesia
来源：
COMPUTERS & ELECTRICAL ENGINEERING | 2018年 / 71卷
关键词：
EMG; WAMP; Kalman filter; Elbow joint angle estimation; Muscle fatigue; MODEL; SEMG;
D O I：
10.1016/j.compeleceng.2018.07.026
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The purpose of this study is to develop and evaluate an adaptive feature to compensate the effect of muscle fatigue in the elbow joint angle estimation. In the experiment protocol, subjects are asked to move the elbow in flexion and extension for 15 min. The electromyography (EMG) signal collected from biceps was extracted using the Wilson amplitude (WAMP) and modified WAMP features. A modified WAMP feature consists of the standard WAMP feature and an adaptive threshold; to smooth the features, the Kalman filter was applied. The results prove that muscle fatigue affects the EMG signal. The RMSEs resulting from the standard WAMP feature in the non-fatigue and fatigue conditions are 12.41 degrees +/- 5.16 degrees and 18.17 degrees +/- 5.53 degrees, respectively. The RMSEs resulting from modified WAMP feature in the non-fatigue and fatigue conditions are 12.63 degrees +/- 5.22 degrees and 13.86 degrees +/- 4.7 degrees, respectively. This proposed method is able to compensate the effect of muscle fatigue on the elbow joint angle estimation.
引用
收藏
页码：284 / 293
页数：10
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