Knee-wearable Robot System Using EMG signals

근전도 신호를 이용한 무릎 착용 로봇시스템

  • Published : 2009.03.01


This paper proposes a knee-wearable robot system for assisting the muscle power of human knee by processing EMG (Electromyogram) signals. Although there are many muscles affecting the knee joint motion, the rectus femoris and biceps femoris among them play a core role in the extension and flexion motion, respectively, of the knee joint. The proposed knee-wearable robot system consists of three parts; the sensor for measuring and processing EMG signals, controller for estimating and applying the required knee torque, and actuator for driving the knee-wearable mechanism. Ultimately, we suggest the motion control method for knee-wearable robot system by processing the EMG signals of corresponding two muscles in this paper. Also, we show the effectiveness of the proposed knee-wearable robot system through the experimental results.


  1. H. Kazerooni, L. Huang, and R. Steger, 'On the control of the Berkeley lower extremity exoskeleton (BLEEX),' IEEE International Conference on Robotics and Automation, pp.4364-4371,2005
  2. H. Kawamoto, S. Lee, S. Kanbe, and Y. Sankai, 'Power assist method for HAL-3 using EMG-based feedback controller,' IEEE International Conference on Systems, Man and Cybernetics, vol. 2, pp. 1648-1653, 2003
  3. H. Kawamoto, S. Kanbe, and Y. Sankai, 'Power assist Method for HAL-3 estimating operator's intention based on motion information,' IEEE International Workshop on Robot and Human Interactive Communication, pp. 67-72, 2003
  5. J. E. Pratt, B. T. Krupp, C. J. Morse, and S. H. Collins, 'The RoboKnee: an exoskeleton for enhancing strength and endurance during walking,' IEEE International Conference on Robotics andAutomation, vol. 3, pp. 2430-2435, 2004
  6. C. Fleischer and G Hommel, Embedded Control System for a Powered Leg Exoskeleton, Springer, 2006
  7. G S. Sawicki, K. E. Gordon, and D. P. Ferris, 'Powered lower limb orthoses: applications in motor adaptation and rehabilitation,' International Conforence on Rehabilitation Robotics, pp.206-211,2005
  8. 위승두 외 편저, 근기능 해부학, 도서출판 대경, 1998
  9. H. Nowmu, Foundation of Medical Instrument, YangSeaKun publishing, 2004
  10. G T. Yamaguchi, Dynamic Modeling of Musculoskeletal Motion, Kluwer Academic publishers, 2001
  11. S. H. Scoot and D. A. Wmter, 'A comparison of three muscle pennation assumptions and their effect on isometric and isotonic force,' Journal of Biomechanics, vol. 24, no. 2, pp. 163-167, 1991
  12. J. Rosen, M. Fuchs, and M. Arcan, 'Performances of hill-type and neural network muscle models-toward a myosignal-based exoskeleton,' Computer a;m Biomedical Research, vol. 32, no.5, pp. 415-439,1999
  13. D. G Lloyd and T. F. Besier, 'An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo,' Journal of Biomechanics, vol. 36, no. 6, pp. 765-776, 2003
  14. E. Clancy and N. Hogan, 'Estimation of joint torque from the surface EMQ' IEEE International Confornence on Engineering in Medicine and Biology Society, pp. 877-878, 1991