• 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