Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
권호 표지
DOI QR코드

DOI QR Code

Development of Five Finger type Myoelectric Hand Prosthesis for State Transition-Based Multi-Hand Gestures change

다중 손동작 변환을 위한 상태 전이 기반 5손가락 근전전동의수 개발

  • Seung-Gi Kim (Korea Orthopedics and Rehabilitation Engineering Center, Korea Workers' Compensation & Welfare Service) ;
  • Sung-Yoon Jung (Korea Orthopedics and Rehabilitation Engineering Center, Korea Workers' Compensation & Welfare Service) ;
  • Beom-ki Hong (Korea Orthopedics and Rehabilitation Engineering Center, Korea Workers' Compensation & Welfare Service) ;
  • Hyun-Jun Shin (Korea Orthopedics and Rehabilitation Engineering Center, Korea Workers' Compensation & Welfare Service) ;
  • Kyoung-Ho Kim (Korea Institute of Robotics & Technology Convergence) ;
  • Se-Hoon Park (Korea Orthopedics and Rehabilitation Engineering Center, Korea Workers' Compensation & Welfare Service)
  • 김승기 (근로복지공단 재활공학연구소) ;
  • 정성윤 (근로복지공단 재활공학연구소) ;
  • 홍범기 (근로복지공단 재활공학연구소) ;
  • 신현준 (근로복지공단 재활공학연구소) ;
  • 김경호 (한국로봇융합연구원) ;
  • 박세훈 (근로복지공단 재활공학연구소)
  • Received : 2024.06.21
  • Accepted : 2024.06.27
  • Published : 2024.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

Various types of assistive devices have been developed for upper limb amputees over the years, with myoelectric prosthesis particularly aimed at improving user convenience by enabling a range of hand gestures beyond simple grasping, tailored to the size and shape of objects. In this study, we developed a five-finger myoelectric prosthesis mimicking human hand size and finger movements, utilizing motor and worm gear mechanisms for stable and independent operation. Based on this, we designed a control system for independent finger control through electromyographic signal input, proposed a state transition-based hand gesture conversion algorithm by selecting representative eight hand gestures and defining conversion condition parameters. We introduced training and usability evaluation methods, and conducted usability assessments among upper limb amputees using dedicated tools, confirming the potential for commercial application of the algorithm and observing adaptive capabilities and high performance through iterative evaluations.

과거부터 상지 절단 장애인을 위한 여러 종류의 보조기가 개발되어 왔으며, 이 중 근전전동의수는 사용자의 편의성 향상을 목적으로 단순 파지 가능 사용에서 물체의 크기와 형태에 따라 다양한 손동작을 변환하여 사용하는 연구가 요구되어 왔다. 본 연구에서는 사람 손 크기와 손가락 움직임을 모사하여 모터와 웜 기어의 구동 메커니즘을 적용한 5 손가락 근전전동의 수를 개발하였다. 이를 바탕으로 근전도 신호 입력을 통한 손가락의 독립적 제어를 위한 제어기를 개발하고, 대표 8가지 손동작 선정, 변환 조건 파라미터 선정을 통한 상태 전이 기반 손동작 변환 알고리즘을 제안하였다. 그리고 훈련과 사용성 평가 방법을 소개하고, 이를 바탕으로 손기능 전용 도구를 이용한 상지 절단 장애인 대상의 사용성 평가를 진행하여 알고리즘의 상용화 가능성을 확인하였으며, 반복적인 평가를 통한 사용자의 적응과 높은 수행 능력을 확인하였다.

Keywords

Acknowledgement

본 연구는 정부(과학기술정보통신부, 산업통상자원부, 보건복지부, 식품의약품안전처)의 재원으로 범부처 전주기의료기기연구개발사업단의 지원을 받아 수행된 연구임(과제고유번호 : RS-2023-KD00238176).

References

  1. Ministry of Health and Welfare. 2023. Registration status of persons with disabilities, http://www.mohw.go.kr/.
  2. J. S. Woo, K. Lionel, S. J. Jung. and W. Y. Chung,"Configuration and Application of a deep learning-based fall detection system," Journal of the Korea Institute of Convergence Signal Processing, vol. 24, no.4, pp. 213-220, 2023, doi:10.23087/jkicsp.2023.24.4.006.
  3. Smit. G, Plettenburg, D. H, "Efficiency of voluntary closing hand and hook prostheses,"Prosthetics and Orthotics International, vol. 34, no. 4, pp. 411-427, 2010, doi:10.3109/03093646.2010.486390.
  4. S. G. Kim, B. K. Hong, et al.,"Development of a hand prosthesis with a heating system to prevent residual limb pain for upper limb amputee,"Journal of Rehabilitation Welfare Engineering & Assistive Technolog, vol. 17, no. 4, pp. 339-349, 2023. doi:10.21288/resko.2023.17.4.339.
  5. S. H. Park, B. K. Hong, J. K. Kim, E. P. Hong, and M. S. Mun, "Development of the myoelectric hand with a 2 DOF auto wrist module," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 17, no. 8, pp. 824- 832, 2011, doi:10.5302/J.ICROS.2011.17.8.824.
  6. S. Y. Jung, S. G. Kim, D. J. Jang, S. K. Kim, S. H. Park, and J. H. Kim, "Development of the Multi-DOF myoelectric hand prosthesis with the intuitive control algorithm,"Journal of the Korean Society for Precision Engineering, vol. 37, no. 2, pp. 139-147, 2020, doi:10.7736/JKSPE.019.083.
  7. Ottobock, Be-Bionic Technical manual, UK, 2017.
  8. I-limb, https://www.ossur.com/en-us/prosthetics.
  9. TASKA, https://www.taskaprosthetics.com/.
  10. J. Li, et al., "Hand gesture recognition based improved multi-channels CNN architecture using EMG sensors," Journal of Intelligent & Fuzzy Systems, vol. 43, pp. 643-656, 2022, doi:10.3233/JIFS-212390.
  11. Y. U. Jo, et al., "Wavelet Transform as Pre-processing for EMG-based Hand Gesture Recognition Suitable for Actual User-environment," Journal of The Institute of Electronics and Information Engineers, vol. 61, no. 4, pp. 63-70, 2024, doi:10.5573/ieie.2024.61.4.63.
  12. J. M. Kim, et al., "sEMG-Based Hand Posture Recognition and Visual Feedback Training for the Forearm Amputee," MDPI, vol. 22, no. 20, 2022, doi:10.3390/s22207984.
  13. A. Toro-Ossaba, et al., "LSTM Recurrent Neural Network for Hand Gesture Recognition Using EMG Signals," MDPI, vol. 12, no. 19, 2022, doi:10.3390/app12199700.
  14. T. Triwiyanto, et al., "Deep Convolution Neural Network to Improve Hand Motion Classifcation Performance Against Varying Orientation Using Electromyography Signal," International Journal of Precision Engineering and Manufacturing, vol. 25, pp. 1289-1301, 2024, doi:10.3390/app12199700.
  15. Z. Brian, R. Dora, S. Robert,"Flexor Pulley System: Anatomy, Injury, and Management," In Journal of Hand Surgery, vol. 39, no. 12, pp. 2525-2532, 2014, doi:10.1016/j.jhsa.2014.06.005.
  16. Maxon, DCX10, https://www.maxongroup.com.
  17. TEXAS INSTRUMENTS, DRV5056 Unipolar Hall Effect Sensor datasheet, 2020.
  18. CHIPSEN, User Manual BOT-CLE310, 2019.
  19. F. Stival, S. Michieletto, M. Cognolato, E. Pagello, H. Muller, and M. Atzori, "A quantitative taxonomy of human hand grasps," Journal of NeuroEngineering and Rehabilitation, vol. 16, no. 1, pp. 1-17, 2019, doi:10.1186/s12984-019-0488-x.
  20. N. Ladha, G. Gaidhani, "Assessment of Hand Function in Post Stroke Patients Using 'Jebsen Taylor Hand Function Test',"Indian Journal of Physiotherapy and Occupational Therapy vol. 15, no. 4, pp. 97-101, 2021, doi:10.37506/ijpot.v15i4.16506.
  21. S. M. Cho, W. S. Kim, N. J. Paik, H. W. Bang, "Upper-Limb Function Assessment Using VBBTs for Stroke Patients,"IEEE Computer Graphics and Applications, vol. 36, no. 1, pp. 70-78, 2016, doi:10.1109/MCG.2015.2.