Skip to main content
SpringerLink
Log in

Development and Validation of a Robotic System Combining Mobile Wheelchair and Lower Extremity Exoskeleton

  • Regular paper
  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

To promote the rehabilitation training occupied at home, in this article, a wheelchair-exoskeleton system combining the lower extremity exoskeleton (LEE) and the mobile wheelchair is developed to help users to complete the activities of daily life. A hierarchical control architecture is designed and developed for the wheelchair-exoskeleton system. The control architecture is composed of three layers: (1) the top layer is achieved by the task-based voice-controlled strategy through voice recognition; (2) the decision layer produces the intent actions based on the output of the top layer; (3) the execution layer is in charge of controlling the movement of the system, including the gait tracking control of LEE as well as the coordination control of the mobile wheelchair. The mobile wheelchair as a partner works in coordination with the LEE by positioning techniques through utilizing ultra-wideband (UWB) sensors. A small validation study with three able-bodied subjects performing the whole usage process is presented. The experimental results demonstrate that the developed wheelchair-exoskeleton system has the potential to be applied to in-home care with long endurance.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Data Availability

Not applicable.

Code Availability

Not applicable.

References

  1. Chen, B., Ma, H., Qin, L.Y., et al.: Recent developments and challenges of lower extremity exoskeletons. J. Orthop. Translat. 5, 26–37 (2016). https://doi.org/10.1016/j.jot.2015.09.007

    Article  Google Scholar 

  2. Díaz, I., Gil, J.J., Sánchez, E., Lower-limb robotic rehabilitation: literature review and challenges. J. Robot. 2011, 1-11 (2011). https://doi.org/10.1155/2011/759764

  3. Kwon, S.H., Lee, B.S., Lee, H.J., Kim, E.J., et al.: Energy efficiency and patient satisfaction of gait with knee-ankle-foot orthosis and robot (ReWalk)-assisted gait in patients with spinal cord injury. Ann. Rehabil. Med. 44, 131–141 (2020). https://doi.org/10.5535/arm.2020.44.2.131

    Article  Google Scholar 

  4. Wang, S.Q., Wang, L.T., Meijneke, C., et al.: Design and Control of the MINDWALKER Exoskeleton. IEEE Trans. Neural Syst. Rehabil. Eng. 23(2), 277–286 (2015). https://doi.org/10.1109/TNSRE.2014.2365697

    Article  Google Scholar 

  5. Kolakowsky-Hayner, S.A., Crew, J., Moran, S., Shah, A.: Safety and feasibility of using the EksoTM bionic exoskeleton to aid ambulation after spinal cord injury. J. Spine 4(3), 1–8 (2013). https://doi.org/10.4172/2165-7939.S4-003

    Article  Google Scholar 

  6. Juszczak, M., Gallo, E., Bushnik, T.: Examining the effects of a powered exoskeleton on quality of life and secondary impairments in people living with spinal cord injury. Top. Spinal Cord Inj. Rehab. 24(3), 336–342 (2018). https://doi.org/10.1310/sci17-00055

    Article  Google Scholar 

  7. Song, Z., Tian, C., Dai, J.S.: Mechanism design and analysis of a proposed wheelchair-exoskeleton hybrid robot for assisting human movement. Mech. Sci. 10, 11–24 (2019). https://doi.org/10.5194/ms-10-11-2019

    Article  Google Scholar 

  8. Borisoff, J.F., Mattie, J., Rafer, V.: Concept proposal for a detachable exoskeleton-wheelchair to improve mobility and health. In: Proc. IEEE International Conference on Rehabilitation Robotics (ICORR), University of Washington, Seattle, WA (2013). https://doi.org/10.1109/ICORR.2013.6650396

  9. Shankar, T., Santosh, K.D.: A Hybrid Assistive Wheelchair- Exoskeleton. In: Proc. International Convention on Rehabilitation Engineering & Assistive Technology, Singapore Therapeutic, Assistive & Rehabilitative Technologies Centre (2015)

  10. Kim, D., Kang, B.B., Kim, K.B., et al.: Eyes are faster than hands: A soft wearable robot learns user intention from the egocentric view. Sci. Robot. 4, essay 2949 (2019). https://doi.org/10.1126/scirobotics.aav2949

  11. Vouga, T., Zhuang, K.Z., Olivier, J., et al.: EXiO—A brain-controlled lower limb exoskeleton for rhesus macaques. IEEE Trans. Neural Syst. Rehabil. Eng. 25(2), 131–141 (2017). https://doi.org/10.1109/TNSRE.2017.2659654

    Article  Google Scholar 

  12. Leonardo, C., Meyer, J.T., Galloway, K.C., et al.: Assisting hand function after spinal cord injury with a fabric-based soft robotic glove. J. Neuroeng. Rehabil. 15(1), 59 (2018). https://doi.org/10.1186/s12984-018-0391-x

    Article  Google Scholar 

  13. Anam, K., A-Jumaily, A.A.: Active exoskeleton control systems: state of the art. Procedia Eng. 41, 988–994 (2012). https://doi.org/10.1016/j.proeng.2012.07.273

    Article  Google Scholar 

  14. Long, Y., Du, Z.J., Cong, L., et al.: Active disturbance rejection control based human gait tracking for lower extremity rehabilitation exoskeleton. ISA Trans. 67, 389–397 (2017). https://doi.org/10.1016/j.isatra.2017.01.006

    Article  Google Scholar 

  15. Zhao, S., Huang, B., Liu, F.: Localization of indoor mobile robot using minimum variance unbiased FIR filter. IEEE Trans. Autom. Sci. Eng. 15, 410–419 (2018). https://doi.org/10.1109/TASE.2016.2599864

    Article  Google Scholar 

  16. Duan, S., Su, R., Xu, C., et al.: Ultra-wideband radio channel characteristics for near-ground swarm robots communication. IEEE Trans. Wirel. Commun. 99, 1–10 (2020). https://doi.org/10.1109/TWC.2020.2986446

    Article  Google Scholar 

  17. Long, Y., Du, Z.J., Chen, C.F., et al.: Development and analysis of an electrically actuated lower extremity assistive exoskeleton. J. Bionic Eng. 14(2), 272–283 (2017). https://doi.org/10.1016/S1672-6529(16)60397-9

    Article  Google Scholar 

  18. Long, Y., Du, Z.J., Wang, W.D., Dong, W.: Human motion intent learning based adaptive motion assistance control for a wearable exoskeleton. Robot. Comput. Integr. Manuf. 49, 317–327 (2018). https://doi.org/10.1016/j.rcim.2017.08.007

  19. Long, Y., Du, Z.J., Wang, W.D., Dong, W.: Development of a wearable exoskeleton rehabilitation system based on hybrid control mode. Int. J. Adv. Rob. Syst. 13(5), 1–13 (2016). https://doi.org/10.1177/1729881416664847

    Article  Google Scholar 

  20. Noronha, B., Dziemian, S., Zito, G.A., Faisal, C. Konnaris, and A.A.: Wink to grasp comparing eye, voice & emg gesture control of grasp with soft robotic gloves. In: Proc. Int. Conf. Rehabil. Robot., pp. 1043–1048 (2017)

  21. Tran, P., Jeong, S., Wolf, S.L., Desai, J.P.: Patient-specific, voice-controlled, robotic FLEXo tendon Glove-II system for spinal cord injury. IEEE Robot. Autom. Lett. 5(2) (2020)

Download references

Funding

This work was supported by the Fundamental Research Funds for the Central Universities (N2129002) and Natural Science Foundation of Guangdong Province (2020A1515110121).

Author information

Authors and Affiliations

  1. Foshan Graduate School of Northeastern University, Foshan, 528000, China

    Yi Long

  2. Faculty of Robot Science and Engineering, Northeastern University, 110000, Shenyang, China

    Yi Long

  3. Zhongshan Walk-best Intelligent Medical Device Co. Ltd, 528400, Zhongshan, China

    Yajun Peng

Authors
  1. Yi Long
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yajun Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Yi Long conceived and designed the study. Yajun Peng performed the experiments. Yi Long written, reviewed and edited the manuscript. All authors read and approved the manuscript.

Corresponding author

Correspondence to Yi Long.

Ethics declarations

Conflicts of Interest/Competing Interests

The authors declare that they have no conflicts of interest.

Ethical Approval

The experiments are performed in the laboratory and ethical approval is granted by the Laboratory Management Council.

Consent to Participate

Not applicable.

Consent to Publish

Not applicable.

Additional information

Publisher’s Note

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

Appendix

Appendix

figure a

Notation: a, b, d, kl and kr are predefined positive parameters, Wl and Wr are the control variables for the left wheel and the right wheel respectively. The other action, e.g., “wheelchair come”, does not judge whether the L3 is bigger or smaller than the defined distance d.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Long, Y., Peng, Y. Development and Validation of a Robotic System Combining Mobile Wheelchair and Lower Extremity Exoskeleton. J Intell Robot Syst 104, 5 (2022). https://doi.org/10.1007/s10846-021-01550-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10846-021-01550-8

Keywords

Search

Navigation