Journal of IKEEE (전기전자학회논문지)

Institute of Korean Electrical and Electronics Engineers (한국전기전자학회)
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A Study on the Mode Change Technique of Intelligent Above-Knee Prosthesis Based on User Intention Capture

지능형 대퇴 의족 사용자의 의도 검출을 통한 제어 모드 변경 기법에 관한 연구

  • Shin, Jin-Woo (Dept. of Electronics Engineering, Korea Polytechnic University) ;
  • Eom, Su-Hong (Dept. of Electronics Engineering, Korea Polytechnic University) ;
  • You, Jung-Hwun (Dept. of Electronics Engineering, Korea Polytechnic University) ;
  • Lee, Eung-Hyuk (Dept. of Electronics Engineering, Korea Polytechnic University)
  • Received : 2020.08.28
  • Accepted : 2020.09.21
  • Published : 2020.09.30
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Abstract

Currently, Intelligent femoral prostheses that support the corresponding mode in walking and specific movements are being studied. Certain controls such as upstairs, sitting, and standing require a technique to classify control commands based on the user's intention because the mode must be changed before the operation. Therefore, in this paper, we propose a technique that can classify various control commands based on the user's intention in the intelligent thigh prosthesis system. If it is determined that the EMG signal needs to be compensated, the proposed technique compensates the EMG signal using the correlation between the strength and frequency components of the normal EMG signal and the muscle volume estimated by the pressure sensor. Through the experiment, it was confirmed that the user's intention was accurately detected even in the situation where muscle fatigue was accumulated. Improved intention detection techniques allow five control modes to be distinguished based on the number of muscle contractions within a given period of time. The results of the experiment confirmed that 97.5% accuracy was achieved through muscle tone compensation even if the strength of the muscle signal was different from normal due to muscle fatigue after exercise.

최근 다양한 환경에서의 보행과 특정 동작에서 해당 모드를 지원하는 지능형 대퇴 의족이 개발되고 있다. 계단 상행, 하행과 같은 특정 제어는 동작 전 모드를 변경해야하기 때문에 사용자의 의도를 기반으로 제어명령을 구분하는 기법이 필요하다. 따라서 본 논문에서는 지능형 대퇴 의족 시스템에서 사용자의 의도에 기반하여 다양한 제어명령을 구분할 수 있는 기법을 제안한다. 제안하는 기법은 근전도 신호의 보상이 필요하다고 판단되는 경우, 평상시의 근전도 신호의 세기 및 주파수 성분과 압력센서로 추정한 근육의 부피 정도의 상관관계를 이용하여 근전도 신호를 보상하는 것이며 실험을 통해 근피로가 축적되어 있는 상황에도 사용자의 의도를 정확하게 검출하는 것을 확인하였다. 향상된 사용자 의도 검출 기법을 통해 정해진 시간 내 근육의 수축 횟수를 기반으로 5개의 제어모드를 구분할 수 있도록 하였으며 실험 결과 운동 후 근피로로 인해 근신호의 세기가 평시와 다를 경우에도 근신호 보상을 통해 97.5%의 정확도를 갖는 것을 확인하였다.

Keywords

References

  1. Kelly MB, Lucy LU, Stephen SK, "Lower extremity characterization of walker-assisted gait in children with spastic diplegic cerebral palsy," Taylor & Francis Group LLC, 2008. DOI: 10.1201/9781420005745.ch10
  2. Alexander, "Gait disorders in older adult. Med SciSports Exerc," pp.992-1008, 1996.
  3. Su, B. Y., Wang, J., Liu, S. Q., Sheng, M., Jiang, J., Xiang, K. "A CNN-Based Method for Intent Recognition Using Inertial Measurement Units and Intelligent Lower Limb Prosthesis," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.27, no.5, pp.1032-1042, 2019. DOI: 10.1109/TNSRE.2019.2909585
  4. Spanias, J. A., Simon, A. M., Finucane, S. B., Perreault, E. J., Hargrove, L. J. "Online adaptive neural control of a robotic lower limb prosthesis," Journal of neural engineering, vol.15, no.1, 2016. DOI: 10.1088/1741-2552/aa92a8
  5. Ottobock, www.ottobock.com
  6. Ossur, www.ossur.kr
  7. Quintero, D., Villarreal, D. J., Lambert, D. J., Kapp, S., Gregg, R. D. "Continuous-phase control of a powered knee-ankle prosthesis: Amputee experiments across speeds and inclines," IEEE Transactions on Robotics, vol.34, no.3, pp.686-701, 2018. DOI: 10.1109/TRO.2018.2794536
  8. Huang, H., Crouch, D. L., Liu, M., Sawicki, G. S., Wang, D. "A cyber expert system for autotuning powered prosthesis impedance control parameters," Annals of biomedical engineering, vol.44, no.5, pp.1613-1624, 2016. DOI: 10.1007/s10439-015-1464-7
  9. Spanias, J. A., Simon, A. M., Ingraham, K. A., Hargrove, L. J, "Effect of additional mechanical sensor data on an EMG-based pattern recognition system for a powered leg prosthesis," 7th International IEEE/EMBS Conference on Neural Engineering (NER), pp.639-642, 2015. DOI: 10.1109/NER.2015.7146704
  10. L. J. Hargrove, A. M. Simon, A. J. Young, R. D. Lipschutz, S. B. Finucane, D. G. Smith, T. A. Kuiken, "Robotic leg control with EMG decoding in an amputee with nerve transfers," New England Journal of Medicine, Vol.369, No.13, pp.1237-1242, 2013. DOI: 10.1056/NEJMoa1300126
  11. Dennis C. Tkach, Aaron J. Young, Lauren H. Smith, Elliott J. Rouse, Levi J. Hargrove, "Real-Time and Offline Performance of Pattern Recognition Myoelectric Control Using a Generic Electrode Grid With Targeted Muscle Reinnervation Patients," IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol.22, pp.727-734, 2014. DOI: 10.1109/TNSRE.2014.2302799
  12. J. L. Pons, R. Ceres, E. Rocon,-, S. Levin, I. Markovits, B. Saro, D. Reynerts, W. Van Moorleghem, L. Bueno, "Virtual reality training and EMG control of the MANUS hand prosthesis," Robotica, Vol.23, pp.311-317, 2005. DOI: https://doi.org/10.1017/S026357470400133X
  13. C. Cipriani, F. Zaccone, S. Micera, M. C. Carrozza, "On the Shared Control of an EMGControlled Prosthetic Hand: Analysis of User- Prosthesis Interaction," IEEE Transactions on Robotics, vol.24, no.1, pp.170-184, 2008. DOI: 10.1109/TRO.2007.910708
  14. Y. Heo, B. K. Hong, E. P. Hong, S. H. Park, M. S. Moon, "Development of a Multi-Function Myoelectric Prosthetic Hand with Communicative Hand Gesture," Journal of Institute of Control, Robotics and Systems, Vol.17, No.12, pp.1248-1255, 2011. DOI: 10.5302/J.ICROS.2011.17.12.1248
  15. Y. H. Kim, S. J. Kim, H. M. Shim, S. M. Lee, "A Method of Muscle Fatigue Analysis for Effective Gait Rehabilitation," Journal of Rehabilitation Welfare Engineering & Assistive Technology, Vol.7, No.1, pp.39-43, 2013.
  16. S. G. Park, M. G. Lee, H. J. Kim, "Comparative Analysis between Soccer Player and Healthy adult man on the Change of the Muscle Fatigue," Journal of Sport and Leisure Studies, Vol.41, No.2, pp.719-727, 2010. https://doi.org/10.51979/KSSLS.2010.08.41.719
  17. K. H. Chon, D. I. Yang, G. Y. Lee, "A study on the Muscle Activity and Fatigue between Quadriceps Femoris Muscle during the Mode Shift of Contraction," Journal of advanced navigation technology, Vol.15, No.6, pp.1152-1162, 2011. DOI: 10.12673/jant.2011.15.6.1152