Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Technical Report
  • Published:

Versatile robotic interface to evaluate, enable and train locomotion and balance after neuromotor disorders

Nature Medicine volume 18, pages 1142–1147 (2012)Cite this article

Subjects

Abstract

Central nervous system (CNS) disorders distinctly impair locomotor pattern generation and balance, but technical limitations prevent independent assessment and rehabilitation of these subfunctions. Here we introduce a versatile robotic interface to evaluate, enable and train pattern generation and balance independently during natural walking behaviors in rats. In evaluation mode, the robotic interface affords detailed assessments of pattern generation and dynamic equilibrium after spinal cord injury (SCI) and stroke. In enabling mode, the robot acts as a propulsive or postural neuroprosthesis that instantly promotes unexpected locomotor capacities including overground walking after complete SCI, stair climbing following partial SCI and precise paw placement shortly after stroke. In training mode, robot-enabled rehabilitation, epidural electrical stimulation and monoamine agonists reestablish weight-supported locomotion, coordinated steering and balance in rats with a paralyzing SCI. This new robotic technology and associated concepts have broad implications for both assessing and restoring motor functions after CNS disorders, both in animals and in humans.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Design and transparency of the robotic interface in healthy rats.
Figure 2: The robotic interface affords detailed assessment of pattern generation and balance.
Figure 3: The robotic postural neuroprosthesis enables skilled motor control after cortical stroke.
Figure 4: The robotic postural neuroprosthesis enables coordinated locomotion on a staircase after moderate and severe SCI.
Figure 5: Training enabled by the robotic postural neuroprosthesis restores equilibrated steering in rats with a severe SCI.

Similar content being viewed by others

References

  1. Courtine, G. et al. Transformation of nonfunctional spinal circuits into functional states after the loss of brain input. Nat. Neurosci. 12, 1333–1342 (2009).

    Article  CAS  Google Scholar 

  2. Harkema, S.J. et al. Human lumbosacral spinal cord interprets loading during stepping. J. Neurophysiol. 77, 797–811 (1997).

    Article  CAS  Google Scholar 

  3. Nessler, J.A. et al. A robotic device for studying rodent locomotion after spinal cord injury. IEEE Trans. Neural. Syst. Rehabil. Eng. 13, 497–506 (2005).

    Article  Google Scholar 

  4. Frey, M. et al. A novel mechatronic body weight support system. IEEE Trans. Neural. Syst. Rehabil. Eng. 14, 311–321 (2006).

    Article  Google Scholar 

  5. Winter, D.A., MacKinnon, C.D., Ruder, G.K. & Wieman, C. An integrated EMG/biomechanical model of upper body balance and posture during human gait. Prog. Brain Res. 97, 359–367 (1993).

    Article  CAS  Google Scholar 

  6. Warren, W.H. Jr., Kay, B.A., Zosh, W.D., Duchon, A.P. & Sahuc, S. Optic flow is used to control human walking. Nat. Neurosci. 4, 213–216 (2001).

    Article  CAS  Google Scholar 

  7. Musselman, K., Brunton, K., Lam, T. & Yang, J. Spinal cord injury functional ambulation profile: a new measure of walking ability. Neurorehabil. Neural Repair 25, 285–293 (2011).

    Article  Google Scholar 

  8. Hidler, J. et al. ZeroG: overground gait and balance training system. J. Rehabil. Res. Dev. 48, 287–298 (2011).

    Article  Google Scholar 

  9. Shetty, D., Fast, A. & Campana, C.A. Ambulatory suspension and rehabilitation apparatus. US patent 7462138 (2008).

  10. Pratt, G.A. et al. Stiffness Isn't Everything. in International Symposium on Experimental Robotics http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.26.3136 (1995).

  11. Vallery, H. et al. Compliant actuation of rehabilitation robots—benefits and limitations of series elastic actuators. IEEE Robot. Autom. Mag. 15, 60–69 (2008).

    Article  Google Scholar 

  12. Harkema, S. et al. Effect of epidural stimulation of the lumbosacral spinal cord on voluntary movement, standing, and assisted stepping after motor complete paraplegia: a case study. Lancet 377, 1938–1947 (2011).

    Article  Google Scholar 

  13. Timoszyk, W.K. et al. Hindlimb loading determines stepping quantity and quality following spinal cord transection. Brain Res. 1050, 180–189 (2005).

    Article  CAS  Google Scholar 

  14. Zörner, B. et al. Profiling locomotor recovery: comprehensive quantification of impairments after CNS damage in rodents. Nat. Methods 7, 701–708 (2010).

    Article  Google Scholar 

  15. Drew, T., Andujar, J.E., Lajoie, K. & Yakovenko, S. Cortical mechanisms involved in visuomotor coordination during precision walking. Brain Res. Rev. 57, 199–211 (2008).

    Article  Google Scholar 

  16. Courtine, G. et al. Recovery of supraspinal control of stepping via indirect propriospinal relay connections after spinal cord injury. Nat. Med. 14, 69–74 (2008).

    Article  CAS  Google Scholar 

  17. Basso, D.M. et al. MASCIS evaluation of open field locomotor scores: effects of experience and teamwork on reliability. Multicenter Animal Spinal Cord Injury Study. J. Neurotrauma 13, 343–359 (1996).

    Article  CAS  Google Scholar 

  18. Musienko, P. et al. Controlling specific locomotor behaviors through multidimensional monoaminergic modulation of spinal circuitries. J. Neurosci. 31, 9264–9278 (2011).

    Article  CAS  Google Scholar 

  19. Kwakkel, G., Kollen, B.J. & Krebs, H.I. Effects of robot-assisted therapy on upper limb recovery after stroke: a systematic review. Neurorehabil. Neural Repair 22, 111–121 (2008).

    Article  Google Scholar 

  20. Duschau-Wicke, A., Caprez, A. & Riener, R. Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training. J. Neuroeng. Rehabil. 7, 43 (2010).

    Article  Google Scholar 

  21. Peearson, K.G. Generating the walking gait: role of sensory feedback. Prog. Brain Res. 143, 123–129 (2004).

    Article  Google Scholar 

  22. Edgerton, V.R. & Roy, R.R. Robotic training and spinal cord plasticity. Brain Res. Bull. 78, 4–12 (2009).

    Article  Google Scholar 

  23. Wessels, M., Lucas, C., Eriks, I. & de Groot, S. Body weight–supported gait training for restoration of walking in people with an incomplete spinal cord injury: a systematic review. J. Rehabil. Med. 42, 513–519 (2010).

    Article  Google Scholar 

  24. Reinkensmeyer, D.J. et al. Tools for understanding and optimizing robotic gait training. J. Rehabil. Res. Dev. 43, 657–670 (2006).

    Article  Google Scholar 

  25. Ada, L., Dean, C.M., Vargas, J. & Ennis, S. Mechanically assisted walking with body weight support results in more independent walking than assisted overground walking in non-ambulatory patients early after stroke: a systematic review. J. Physiother. 56, 153–161 (2010).

    Article  Google Scholar 

  26. Colgate, E. & Hogan, N. An analysis of contact instability in terms of passive physical equivalents. Proc. IEEE Int. Conf. Robot. Autom. doi:10.1109/ROBOT.1989.100021 (1989).

Download references

Acknowledgements

We would like to acknowledge the excellent technical help provided by J. Heutschi, N. Wenger, M. Hürlimann, Q. Barraud and S. Duis for data collection and care of the rats, as well as A.S. Tafreshi for the design of the user interface to control the robotic system and A. Brunschweiler, A. Rotta and M. Fritschi for the realization of the suspension system. This work was supported by the National Centers of Competence in Research “Neural Plasticity and Repair” and “Robotics” of the Swiss National Science Foundation, the European Research Council (ERC 261247, “Walk Again”), European Community's Seventh Framework Programme (CP-IP 258654, NeuWALK), the Christopher and Dana Reeve Foundation and the Swiss National Science Foundation (subside 310030_130850).

Author information

Author notes

  1. Nadia Dominici and Urs Keller: These authors contributed equally to this work.

Authors and Affiliations

  1. Neurology Department, University of Zurich, Zurich, Switzerland

    Nadia Dominici, Lucia Friedli, Rubia van den Brand, Pavel Musienko & Grégoire Courtine

  2. Center for Neuroprosthetics and Brain Mind Institute, School of Life Science, Swiss Federal Institute of Technology, Lausanne, Switzerland

    Nadia Dominici, Lucia Friedli, Rubia van den Brand, Pavel Musienko & Grégoire Courtine

  3. Sensory-Motor Systems Lab, Institute of Robotics and Intelligent Systems, Swiss Federal Institute of Technology, Zurich, Switzerland

    Urs Keller, Heike Vallery & Robert Riener

  4. Department of Biomedical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates

    Heike Vallery

  5. Brain Research Institute, University of Zurich, Zurich, Switzerland

    Michelle L Starkey

  6. Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Switzerland

    Michelle L Starkey & Robert Riener

  7. Pavlov Institute of Physiology, St. Petersburg, Russia

    Pavel Musienko

Authors
  1. Nadia Dominici
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Urs Keller
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Heike Vallery
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lucia Friedli
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rubia van den Brand
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Michelle L Starkey
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Pavel Musienko
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Robert Riener
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Grégoire Courtine
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

U.K., H.V., R.R. and G.C. conceived of and designed the robotic interface. P.M., M.L.S. and G.C. performed the surgeries. N.D. and G.C. conceived of the experiments, analyzed the data and prepared the figures with the help of the other authors. N.D., L.F., R.v.d.B. trained the rats and collected the data. G.C. wrote the manuscript, and all the authors contributed to its editing. G.C. supervised all aspects of the work.

Corresponding author

Correspondence to Grégoire Courtine.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–10 and Supplementary Table 1 (PDF 8470 kb)

Supplementary Video 1

Design and validation of the robotic interface (MOV 18902 kb)

Supplementary Video 2

Evaluation of optimal support conditions for motor pattern generation in spinal rats (MOV 19058 kb)

Supplementary Video 3

Evaluation of balance control capacities after a cortical stroke (MOV 7764 kb)

Supplementary Video 4

Propulsive neuroprosthetic interface (MOV 9793 kb)

Supplementary Video 5

Postural neuroprosthetic interface to enable precise paw placement after a cortical stroke (MOV 6650 kb)

Supplementary Video 6

Postural neuroprosthetic interface to enable coordinated locomotion in rats with a cervical hemisection (MOV 8024 kb)

Supplementary Video 7

Postural neuroprosthetic interface to enable coordinated locomotion in rats with paralyzing SCI (MOV 9977 kb)

Supplementary Video 8

Robot-enabled locomotor training restores equilibrated steering in rats with paralyzing SCI (MOV 24035 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dominici, N., Keller, U., Vallery, H. et al. Versatile robotic interface to evaluate, enable and train locomotion and balance after neuromotor disorders. Nat Med 18, 1142–1147 (2012). https://doi.org/10.1038/nm.2845

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nm.2845

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing