Skip to main content
Log in

Upper-Limb Tele-Rehabilitation System with Force Sensorless Dynamic Gravity Compensation

  • Published:
International Journal of Social Robotics Aims and scope Submit manuscript

Abstract

Tele-rehabilitation provides remote physiotherapy services for patients who have limited access to hospitals. This paper proposes a sensorless tele-rehabilitation system for the upper-limb using two robots in master–slave configuration. The system provides a transparent haptic feeling between the therapist and the patient by simultaneous tracking of both position and torque. The torque is measured using the reaction torque observer. Furthermore, an online recursive numerical parameter estimation method is proposed to identify the gravity disturbance in bilateral teleoperation. The system automatically estimates the parameters using the reaction torque observer output’s data while the therapist is delivering remote physiotherapy services. The estimated gravity torque is compensated in the system as an improvement of the transparency of the teleoperated system. Therefore the therapist would feel only the abnormalities of the patient’s arm. Estimated parameters automatically update the system and enhance the performance. The proposed method was practically verified with a master slave tele-rehabilitation system. Results suggest the applicability of the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Plautz EJ, Milliken GW, Nudo RJ (2000) Effects of repetitive motor training on movement representations in adult squirrel monkeys: role of use versus learning. Neurobiol Learn Mem 74(1):27

    Article  Google Scholar 

  2. Stucki G, Stier-Jarmer M, Grill E, Melvin J (2005) Rationale and principles of early rehabilitation care after an acute injury or illness. Disabil Rehabil 27(7–8):353

    Article  Google Scholar 

  3. Babaiasl M, Mahdioun SH, Jaryani P, Yazdani M (2016) A review of technological and clinical aspects of robot-aided rehabilitation of upper-extremity after stroke. Disabil Rehabil Assist Technol 11(4):263

    Google Scholar 

  4. Prange GB, Jannink MJ, Groothuis-Oudshoorn CG, Hermens HJ, IJzerman MJ (2006) Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. J Rehabil Res Dev 43(2):171

    Article  Google Scholar 

  5. Volpe B, Krebs H, Hogan N, Edelstein L, Diels C, Aisen M (2000) A novel approach to stroke rehabilitation robot-aided sensorimotor stimulation. Neurology 54(10):1938

    Article  Google Scholar 

  6. Cherry CO, Chumbler NR, Richards K, Huff A, Wu D, Tilghman LM, Butler A (2017) Expanding stroke telerehabilitation services to rural veterans: a qualitative study on patient experiences using the robotic stroke therapy delivery and monitoring system program. Disabil Rehabil Assist Technol 12(1):21

    Article  Google Scholar 

  7. Zhang S, Guo S, Gao B, Hirata H, Ishihara H (2015) Design of a novel telerehabilitation system with a force-sensing mechanism. Sensors 15(5):11511

    Article  Google Scholar 

  8. Park HS, Peng Q, Zhang LQ (2008) A portable telerehabilitation system for remote evaluations of impaired elbows in neurological disorders. IEEE Trans Neural Syst Rehabil Eng 16(3):245

    Article  Google Scholar 

  9. Song A, Wu C, Ni D, Li H, Qin H (2016) One-therapist to three-patient telerehabilitation robot system for the upper limb after stroke. Int J Soc Robot 8(2):319

    Article  Google Scholar 

  10. Song A, Pan L, Xu G, Li H (2015) Adaptive motion control of arm rehabilitation robot based on impedance identification. Robotica 33(9):1795

    Article  Google Scholar 

  11. Just F, Özen Ö, Tortora S, Riener R, Rauter G (2017) Feedforward model based arm weight compensation with the rehabilitation robot ARMin. In: Rehabilitation robotics (ICORR), 2017 international conference on, IEEE, pp 72–77

  12. Moubarak S, Pham MT, Moreau R, Redarce T (2010) Gravity compensation of an upper extremity exoskeleton. In: Engineering in medicine and biology society (EMBC), 2010 annual international conference of the IEEE, IEEE, pp 4489–4493

  13. Ugurlu B, Nishimura M, Hyodo K, Kawanishi M, Narikiyo T (2015) Proof of concept for robot-aided upper limb rehabilitation using disturbance observers. IEEE Trans Hum Mach Syst 45(1):110

    Article  Google Scholar 

  14. Abeykoon AHS, Ruwanthika RM (2016) Remote gripping for effective bilateral teleoperation. In: Handbook of research on human–computer interfaces, developments, and applications, IGI Global, pp 99–134

  15. Takei T, Shimono T, Kubo R, Nishi H, Ohnishi K (2008) Gravity compensation for improvement of operationarity in bilateral teleoperation. IEEJ Trans Ind Appl 128(6):767–774

    Article  Google Scholar 

  16. Nishimura K, Ohnishi K (2006) Gravity estimation and compensation of grasped object for bilateral teleoperation. In: Advanced motion control, 2006. 9th IEEE international workshop on, IEEE, pp 72–77

  17. El Kalam AA, Ferreira A, Kratz F (2016) Bilateral teleoperation system using QoS and secure communication networks for telemedicine applications. IEEE Syst J 10(2):709

    Article  Google Scholar 

  18. Just F, Baur K, Riener R, Klamroth-Marganska V, Rauter G (2016) Online adaptive compensation of the ARMin Rehabilitation Robot. In: Biomedical robotics and biomechatronics (BioRob), 2016 6th IEEE international conference on, IEEE, pp 747–752

  19. Katsura S, Matsumoto Y, Ohnishi K (2007) Modeling of force sensing and validation of disturbance observer for force control. IEEE Trans Ind Electron 54(1):530

    Article  Google Scholar 

  20. Mizuochi M, Tsuji T, Ohnishi K (2006) Improvement of disturbance suppression based on disturbance observer. In: 9th IEEE international workshop on advanced motion control, 2006, IEEE, pp 229–234

  21. Perera GA, Pillai MB, Harsha A, Abeykoon S (2014) DC motor inertia estimation for robust bilateral control. In: Information and automation for sustainability (ICIAfS), 2014 7th international conference on, IEEE, pp 1–7

  22. Ohnishi K, Matsui N, Hori Y (1994) Estimation, identification, and sensorless control in motion control system. Proc IEEE 82(8):1253

    Article  Google Scholar 

  23. Chinthaka MD, Abeykoon AHS (2015) Friction compensation of DC motors for precise motion control using disturbance observer. ECTI Trans Comput Inf Technol (ECTI-CIT) 9(1):74

    Google Scholar 

  24. Ohnishi K, Shibata M, Murakami T (1996) Motion control for advanced mechatronics. IEEE/ASME Trans Mechatron 1(1):56

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to P. A. Diluka Harischandra.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Harischandra, P.A.D., Abeykoon, A.M.H.S. Upper-Limb Tele-Rehabilitation System with Force Sensorless Dynamic Gravity Compensation. Int J of Soc Robotics 11, 621–630 (2019). https://doi.org/10.1007/s12369-019-00522-1

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12369-019-00522-1

Keywords

Navigation