The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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NREH: Upper Extremity Rehabilitation Robot for Various Exercises and Data Collection at Home

NREH: 다양한 운동과 데이터 수집이 가능한 가정용 상지재활로봇

  • Jun-Yong Song (Department of Rehabilitative & Assistive Technology, National Rehabilitation Center) ;
  • Seong-Hoon Lee (Department of Rehabilitative & Assistive Technology, National Rehabilitation Center) ;
  • Won-Kyung Song (Department of Rehabilitative & Assistive Technology, National Rehabilitation Center)
  • Received : 2023.08.04
  • Accepted : 2023.10.20
  • Published : 2023.11.30
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Abstract

In this paper, we introduce an upper extremity rehabilitation robot, NREH (NRC End-effector based Rehabilitation arm at Home). Through NREH, stroke survivors could continuously exercise their upper extremities at home. NREH allows a user to hold the handle of the end-effector of the robot arm. NREH is a end-effector-based robot that moves the arm on a two-dimensional plane, but the tilt angle can be adjusted to mimic a movement similar to that in a three-dimensional space. Depending on the tilting angle, it is possible to perform customized exercises that can adjust the difficulty for each user. The user can sit down facing the robot and perform exercises such as arm reaching. When the user sits 90 degrees sideways, the user can also exercise their arms on a plane parallel to the sagittal plane. NREH was designed to be as simple as possible considering its use at home. By applying error augmentation, the exercise effect can be increased, and assistance force or resistance force can be applied as needed. Using an encoder on two actuators and a force/torque sensor on the end-effector, NREH can continuously collect and analyze the user's movement data.

Keywords

Acknowledgement

This project was supported by the Research Program of National Rehabilitation Research Institute, Korea National Rehabilitation Center [NRCTR-IN18006, NRCTR-IN19006, NRCTR-IN20006, NRCTR-IN21005, NRCTR-IN22004]

References

  1. C. E. Han, S. Kim, S. Chen, Y.-H. Lai, J.-Y. Lee, R. Osu, C. J. Winstein, and N. Schweighofer, "Quantifying arm nonuse in individuals poststroke," Neurorehabilitation and neural repair, vol. 27, no. 5, pp. 439-447, Jun., 2013, DOI: 10.1177/1545968312471904. 
  2. A. C. Plummer, "Constraint-induced therapy and the motor learning literature that underpins its application," Physical therapy reviews, vol. 8, no. 3, pp. 143-149, Jul., 2003, DOI: 10.1179/108331903225002498. 
  3. G. Kwakkel, R. Peppen, R. C. Wagenaar, S. W. Dauphinee, C. Richards, A. Ashburn, K. Miller, N. Lincoln, C. Partridge, I. Wellwood, and P. Langhorne, "Effects of augmented exercise therapy time after stroke: a meta-analysis," Stroke, vol. 35, no. 11, pp. 2529-2539, Oct., 2004, DOI: 10.1161/01.STR.0000143153.76460.7d. 
  4. DIH Medical Group, Hocoma, [Online], https://www.hocoma.com/us/solutions/arm-hand/, Accessed: Mar. 24, 2023. 
  5. J.-Y. Song, S.-H. Lee, and W.-K. Song, "Improved Wearability of the Upper Limb Rehabilitation Robot NREX with respect to Shoulder Motion," The Journal of Korea Robotics Society, vol. 14, no. 4, pp. 318-325, Nov., 2019, DOI: 10.7746/jkros.2019.14.4.318. 
  6. J.-Y. Song and W.-K. Song, "Improvement of Upper Limb Rehabilitation Robot NREH Device at Home," The 15th Korea Robotics Society Annual Conference, Pyeongchang, Gangwon-do, Republic of Korea, 2020, [Online], https://www.nl.go.kr/. 
  7. Y. Wei, J. Patton, P. Bajaj, and R. Scheidt, "A real-time haptic/graphic demonstration of how error augmentation can enhance learning," IEEE international conference on robotics and automation, Barcelona, Spain, pp. 4406-4411, Apr., 2005, DOI: 10.1109/ROBOT.2005.1570798. 
  8. F. Abdollahi, E. D. C. Lazarro, M. Listenberger, R. V. Kenyon, M. Kovic, R. A. Bogey, D. Hedeker, B. D. Jovanovic, and J. L. Patton, "Error augmentation enhancing arm recovery in individuals with chronic stroke: a randomized crossover design," Neurorehabilitation and neural repair, vol. 28, no. 2, pp. 120-128, Aug., 2013, DOI: 10.1177/1545968313498649. 
  9. L. Li, Q. Fu, S. Tyson, N. Preston, and A. Weightman, "A scoping review of design requirements for a home-based upper limb rehabilitation robot for stroke," Topics in Stroke Rehabilitation, vol. 29, no. 6, pp. 449-463, Jul., 2021, DOI: 10.1080/10749357.2021.1943797. 
  10. M.-R. Hong and W.-K. Song, "Usability Test of Upper limb Rehabilitation Robot NREH using Visual Error Augmentation," The 14th Korea Robotics Society Annual Conference, Pyeongchang, Gangwon-do, Republic of Korea, 2019, [Online], https://www.nl.go.kr/. 
  11. W.-K. Song and J. Song, "Improvement of upper extremity rehabilitation Robotic Exoskeleton, NREX," 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), Jeju, Republic of Korea, 2017, DOI: 10.1109/URAI.2017.7992674. 
  12. S.-H. Lee, J.-Y. Song, and W.-K. Song, "Control of Upper Limb Rehabilitation Robot NREH using Force Sensor," The 15th Korea Robotics Society Annual Conference, Pyeongchang, Gangwon-do, Republic of Korea, 2020, [Online], https://www.nl.go.kr/. 
  13. T. B. Dijkhuis, F. J. Blaauw, M. W. V. Ittersum, H. Velthuijsen, and M. Aiello, "Personalized physical activity coaching: a machine learning approach," Sensors, vol. 18, no. 2, Feb., 2018, DOI: 10.3390/s18020623.