한국정밀공학회지 (Journal of the Korean Society for Precision Engineering)

  • 제30권8호
  • /
  • Pages.870-877
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  • 2013
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  • 1225-9071(pISSN)
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  • 2287-8769(eISSN)
한국정밀공학회 (Korean Society for Precision Engineering)
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인간-기계 인터페이스를 위한 근 부피 센서 개발

Development of the MVS (Muscle Volume Sensor) for Human-Machine Interface

  • Lim, Dong Hwan (Department of Mechanical Engineering, Hanyang Univ.) ;
  • Lee, Hee Don (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 Robot Engineering, Hanyang Univ.) ;
  • An, Jae Yong (Department of Pathology and Orthopedics, Cheil General Hospital, Kwandong Univ.)
  • 투고 : 2013.01.21
  • 심사 : 2013.07.17
  • 발행 : 2013.08.01
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초록

There has been much recent research interest in developing numerous kinds of human-machine interface. This field currently requires more accurate and reliable sensing systems to detect the intended human motion. Most conventional human-machine interface use electromyography (EMG) sensors to detect the intended motion. However, EMG sensors have a number of disadvantages and, as a consequence, the human-machine interface is difficult to use. This study describes a muscle volume sensor (MVS) that has been developed to measure variation in the outline of a muscle, for use as a human-machine interface. We developed an algorithm to calibrate the system, and the feasibility of using MVS for detecting muscular activity was demonstrated experimentally. We evaluated the performance of the MVS via isotonic contraction using the KIN-COM$^{(R)}$ equipment at torques of 5, 10, and 15 Nm.

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참고문헌

  1. Sato, T., Nishida, Y., Ichikawa, J., Hatamura, Y., and Mizoguchi, H., "Active understanding of human intention by a robot through monitoring of human behavior," Proc. of the IEEE/RSJ/GI International Conference on Intelligent Robots and systems, Vol. 1, pp. 405-414, 1994.
  2. Cooper, R., Osselton, J. W., and Shaw, J. C., "EEG Technology," Butterworths, 3rd edition, pp.1-10, 1980.
  3. De Luca, C. J., "Physiology and mathematics of myoelectric signals." IEEE Transactions on Biomedical Engineering, Vol. BME-26, No. 6, pp. 313-325, 1979. https://doi.org/10.1109/TBME.1979.326534
  4. Rushmer, R. F., "Cardiovascular Dynamics," WB Saunders, 4th edition, pp. 33-58, 1976.
  5. Mulas, M., Folgheraiter, M., and Gini, G., "An EMG controlled exoskeleton for hand rehabilitation," Rehabilitation Robotics, pp. 371-374, 2005.
  6. Seo, A. R, Jang, H. Y., Kim, W. S., Han, C. S., and Han, J. S., "Development and verification of a volume sensor for measuring human behavior," Int. J. Precis. Eng. Manuf., Vol. 13, No. 6, pp. 899-904, 2012. https://doi.org/10.1007/s12541-012-0117-0
  7. Moromugi, S., Kim, S. H., Yoon, S. J., Matsuzaka, N., Ishimatsu, T., and Lawn, M. J., "Development of an effective training machine using muscle activity information," IEEE Industrial Electronics, pp. 4534- 4539, 2006.
  8. Koyama, T., Tanaka, T., Kaneko, S., Moromugi, S., and Feng, M. Q., "Integral Ultrasonic Muscle Activity Sensor for Detecting Human Motion," Proc. of the IEEE International Conference on System, Man and Cybernetics, Vol. 2, pp. 1669-1674, 2005.
  9. Cen, L., Han, H. Y., and Kim, J., "Optical muscle activation sensors for estimating upper limb force level," Proc. of IEEE Instrumentation and Measurement Technology Conference, pp. 1-4, 2011.
  10. Richard, L. L., "Skeletal Muscle Structure, Function, and Plasticity," Lippincott, 2nd Ed., pp. 113-172, 2002.
  11. Epstein, M. and Herzog, W., "Theoretical Models of Skeletal Muscle," John Wiley & Sons, pp. 26-27, 1998.
  12. Fukunaga, T., Miyatani, M., Tachi, M., Kouzaki, M., Kawakami, Y., and Kanehisa, H., "Muscle volume is a major determinant of join torque in humans," Acta Physiol Scand, pp. 249-255, 2001.