DocumentCode
3459609
Title
Prediction of Human Elbow Torque from EMG Using SVM Based on AWR Information Acquisition Platform
Author
Song, Quanjun ; Sun, Bingyu ; Lei, Jianhe ; Gao, Zhen ; Yu, Yong ; Liu, Ming ; Ge, Yunjian
Author_Institution
Inst. of Intell. Machine, Chinese Acad. of Sci., Hefei
fYear
2006
fDate
20-23 Aug. 2006
Firstpage
1274
Lastpage
1278
Abstract
In this paper a novel prediction method of elbow torque from EMG signal using SVM is proposed. How to model the relations between EMG signals and various kinematical aspects of the movement behavior is a difficult problem in the researches of neurophysiology and biomechanics. Traditional prediction methods include using neural networks to model the relations. However, these methods suffer from several problems, such as local minima, the difficulty of the selection of the model, etc. To address these problems, support vector machine is adopted to construct the nonlinear model. The efficiency of our proposed method is proved by experiment results.
Keywords
biomechanics; electromyography; neurophysiology; support vector machines; AWR Information Acquisition Platform; EMG; biomechanics; human elbow torque; neurophysiology; support vector machine; Biomechanics; Elbow; Electromyography; Humans; Neural networks; Neurophysiology; Prediction methods; Predictive models; Support vector machines; Torque; EMG; Information Acquisition; Support Vector Machine; joint Torque;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Acquisition, 2006 IEEE International Conference on
Conference_Location
Shandong
Print_ISBN
1-4244-0528-9
Electronic_ISBN
1-4244-0529-7
Type
conf
DOI
10.1109/ICIA.2006.305933
Filename
4097866
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