Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
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Estimation of Shoulder Flexion Torque and Angle from Surface Electromyography for Physical Human-Machine Interaction

물리적 인간-기계 상호작용을 위한 표면 근전도 신호 기반의 어깨 굴곡 토크 및 각도 추정

  • Park, Ki-Han (Department of Mechanical Engineering, KAIST) ;
  • Lee, Dong-Ju (Department of Mechanical Engineering, KAIST) ;
  • Kim, Jung (Department of Mechanical Engineering, KAIST)
  • 박기한 (한국과학기술원 기계공학과) ;
  • 이동주 (한국과학기술원 기계공학과) ;
  • 김정 (한국과학기술원 기계공학과)
  • Received : 2011.03.30
  • Accepted : 2011.04.28
  • Published : 2011.06.01
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Abstract

This paper examines methods to estimate torque and angle in shoulder flexion from surface electromyography(sEMG) signals for intuitive and delicate control of robotic assistance device. Five muscles on the upper arm, three for shoulder flexion and two for shoulder extension, were used to offer favorable sEMG recording conditions in the estimation. The methods tested were the mean absolute value (MAV) with linear regression and the artificial neural network (ANN) method. An optimal condition was sought by varying combination of muscles used and the parameters in each method. The estimation performance was evaluated using the correlation values and normalized root mean square error values. In addition, we discussed their possible use as an estimation of motion intent of a user or as a command input in a physical human-machine interaction system.

Keywords

References

  1. Choi, C., Shin M., Kwon, S. and Kim, J., "EMGbased Real-time Finger Force Estimation for Human-Machine Interaction," J. of KSPE, Vol. 26, No. 8, pp. 132-141, 2009.
  2. Dellon, B. and Matsuoka, Y., "Prosthetics, Exoskeletons, and Rehabilitation - Now and for the Future," IEEE Robotics & Automation Magazine, Vol. 14, No. 1, pp. 30-34, 2007.
  3. Cipriani, C., Zaccone, F., Micera, S. and Carrozza, M. C., "On the Shared Control of an Emg-Controlled Prosthetic Hand: Analysis of User-Prosthesis Interaction," IEEE Trans. Robotics, Vol. 24, No. 1, pp. 170-184, 2008. https://doi.org/10.1109/TRO.2007.910708
  4. Artemiadis, P. K. and Kyriakopoulos, K. J., "Emg- Based Teleoperation of a Robot Arm in Planar Catching Movements Using Armax Model and Trajectory Monitoring Techniques," Proc. IEEE Int. Conf. Robotics and Automation, pp. 3244-3249, 2006.
  5. Cavanagh, P. R. and Komi, P. V., "Electromechanical Delay in Human Skeletal Muscle under Concentric and Eccentric Contractions," Eur. J. Appl. Physiol. Occup. Physiol., Vol. 42, No. 3, pp. 159-163, 1979. https://doi.org/10.1007/BF00431022
  6. Maier, M. A. and Hepp-Reymond, M. C., "Emg Activation Patterns During Force Production in Precision Grip. Ii. Muscular Synergies in the Spatial and Temporal Domain," Exp. Brain Res., Vol. 103, No. 1, pp. 123-136, 1995. https://doi.org/10.1007/BF00241970
  7. Nagata, K., Ando, K., Magatani, K. and Yamada, M., "Development of the Hand Motion Recognition System Based on Surface Emg Using Suitable Measurement Channels for Pattern Recognition," Proc. 29th Annu. Int. Conf. IEEE EMBS, pp. 5214-5217, 2007.
  8. Staudenmann, D., Kingma, I., Daffertshofer, A., Stegeman, D. F. and Van Dieen, J. H., "Improving Emg-Based Muscle Force Estimation by Using a High-Density EMG Grid and Principal Component Analysis," IEEE Trans. Biomed. Eng., Vol. 53, No. 4, pp. 712-719, 2006. https://doi.org/10.1109/TBME.2006.870246
  9. Mobasser, F., Eklund, J. M. and Hashtrudi-Zaad, K., "Estimation of Elbow-Induced Wrist Force with Emg Signals Using Fast Orthogonal Search," IEEE Trans. Biomed. Eng., Vol. 54, No. 4, pp. 683-693, 2007. https://doi.org/10.1109/TBME.2006.889190
  10. Tenore, F., Ramos, A., Fahmy, A., Acharya, S., Etienne-Cummings, R. and Thakor, N. V., "Towards the Control of Individual Fingers of a Prosthetic Hand Using Surface Emg Signals," Proc. 29th Annu. Int. Conf. IEEE EMBS, pp. 6145-6148, 2007.
  11. Valero-Cuevas, F. J., Zajac, F. E. and Burgar, C. G., "Large Index-Fingertip Forces Are Produced by Subject-Independent Patterns of Muscle Excitation," J. Biomech., Vol. 31, No. 8, pp. 693-703, 1998. https://doi.org/10.1016/S0021-9290(98)00082-7
  12. Maier, M. A. and Hepp-Reymond, M. C., "Emg Activation Patterns During Force Production in Precision Grip. I. Contribution of 15 Finger Muscles to Isometric Force," Exp. Brain Res., Vol. 103, No. 1, pp. 108-122, 1995. https://doi.org/10.1007/BF00241969
  13. Yoon, W. and Kim, J., "Estimation of elbow flexion force during isometric muscle contraction from mechanomyography and electromyography," Med. Biol. Eng. Compt. Vol. 48, No. 11, pp. 1149-1157, 2010. https://doi.org/10.1007/s11517-010-0641-y
  14. Yoon, W. and Kim, J., "Feasibility of using an artificial neural network model to estimate the elbow flexion force from mechanomyography," J. Neuroscience Methods, Vol. 194, No. 2, pp. 386-393, 2011. https://doi.org/10.1016/j.jneumeth.2010.11.003
  15. Merletti, R. and Parker, P., "Elctromyography : physiology, engineering, and noninvasive applications," John Wiley & Sons, 2004.