Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
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Joint Torque Estimation of Elbow joint using Neural Network Back Propagation Theory

역전파 신경망 이론을 이용한 팔꿈치 관절의 관절토크 추정에 관한 연구

  • Jang, Hye-Youn (Department of Mechanical Engineering, Hanyang Univ.) ;
  • Kim, Wan-Soo (Department of Mechanical Engineering, Hanyang Univ.) ;
  • Han, Jung-Soo (Department of Mechanical System Engineering, Hansung Univ.) ;
  • Han, Chang-Soo (Department of Mechanical Engineering, Hanyang Univ.)
  • Received : 2011.03.30
  • Accepted : 2011.04.28
  • Published : 2011.06.01
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Abstract

This study is to estimate the joint torques without torque sensor using the EMG (Electromyogram) signal of agonist/antagonist muscle with Neural Network Back Propagation Algorithm during the elbow motion. Command Signal can be guessed by EMG signal. But it cannot calculate the joint torque. There are many kinds of field utilizing Back Propagation Learning Method. It is generally used as a virtual sensor estimated physical information in the system functioning through the sensor. In this study applied the algorithm to obtain the virtual senor values estimated joint torque. During various elbow movement (Biceps isometric contraction, Biceps/Triceps Concentric Contraction (isotonic), Biceps/Triceps Concentric Contraction/Eccentric Contraction (isokinetic)), exact joint torque was measured by KINCOM equipment. It is input to the (BP)algorithm with EMG signal simultaneously and have trained in a variety of situations. As a result, Only using the EMG sensor, this study distinguished a variety of elbow motion and verified a virtual torque value which is approximately(about 90%) the same as joint torque measured by KINCOM equipment.

Keywords

References

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