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A study to understand lead-lag performance of subject vs rehabilitation system

Published:08 March 2012Publication History

ABSTRACT

Robotic assistance in stroke rehabilitation is rapidly advancing based on the recent developments in robotics, haptic interfaces and virtual reality. GENTLE/S is a rehabilitation system that utilized haptic and virtual reality technologies to deliver challenging and meaningful therapies to upper limb impaired stroke subjects. The current research is working towards designing GENTLE/A system with a better adaptive human-robot interface, which allows for automatic tuning of the assistance and resistance based on provided input. This paper presents the results from a preliminary study conducted with three healthy subjects as part of this research. The aim of the investigation is to explore whether it is possible to identify if a robot or a person is leading the interaction by comparing the results from the actual performance of the subject with the minimum jerk model used to drive the robot. The final goal is to use these observations to probe various ways in which the contribution of robot can be established and the adaptability of the robot during the therapy can be enhanced.

References

  1. Effects of Stroke. Retrieved Jan 10, 2012, from National Stroke Association (NSA): http://www.stroke.orgGoogle ScholarGoogle Scholar
  2. Krakauer, J. 2006. Motor learning: its relevance to stroke recovery and neurorehabilitation. J. of Current Opinion in Neurology, 19, 1 (2006), 84--90.Google ScholarGoogle ScholarCross RefCross Ref
  3. Fasoli, S., Krebs, H., Stein, J., Frontera, W., Hughes, R. and Hogan, N. 2004. Robotic therapy for chronic motor impairments after stroke: follow-up results. Arch of Phys Med Rehabil, 85 (2004), 1106--1111.Google ScholarGoogle ScholarCross RefCross Ref
  4. Aisen, M., Krebs, H., Hogan, N., McDowell, F. and Volpe, B. 1997. The Effect of Robot-Assisted Therapy and Rehabilitative Training on Motor Recovery Following Stroke. Archives of Neurology, 54, 4 (1997), 443--446.Google ScholarGoogle ScholarCross RefCross Ref
  5. Krebs, H., Hogan, N., Aisen, M. and Volpe, B. 1998. Robot-Aided Neurorehabilitaion. J. of IEEE Trans Rehab Eng, 6 (1998), 75--87.Google ScholarGoogle ScholarCross RefCross Ref
  6. Volpe, B., Krebs, H., Hogan, N., Edelsteinn, L., Diels, C. and Aisen, M. 1999. Robot training enhanced motor outcome in patients with stroke maintained over 3 years. J. of Neurology, 53, 8 (1999), 1874--1876.Google ScholarGoogle ScholarCross RefCross Ref
  7. Burgar, C. G., Lum, P. S., Shor, P. C. and Van der Loos, H. F. M. 2000. Development of robots for rehabilitation therapy: The Palo Alto VA/Stanford experience. J. of Rehabilitation Research and Development, 37, 6 (2000), 663--673.Google ScholarGoogle Scholar
  8. Lum, P., Burgar, C., Shor, P., Majmundar, M. and Loos, M. V. d. 2002. Robot-Assisted Movement Training Compared With Conventional Therapy Techniques for the Rehabilitation of Upper- Limb Function After Stroke. Arch. of Phys Med Rehabil, 83 (2002), 952--959.Google ScholarGoogle Scholar
  9. Lum, P., Burgar, C. and Shor, P. 2004. Evidence for Improved Muscle Activation Patterns After Retraining of Reaching Movements with the MIME Robotic System in Subjects with Post-Stroke Hemiparesis. IEEE Trans on Neural Systems and Rehabil Eng, 12, 2 (2004), 186--194.Google ScholarGoogle ScholarCross RefCross Ref
  10. Lum, P., Burgar, C., Loos, M. V. d., Shor, P., Majumdar, M. and Yap, R. 2005. The MIME robotic system for upper-limb neuro-rehabilitation: results from a clinical trial in subacute stroke. In Proceedings of ICORR (Chicago, Illinois, June 28-Jul 1, 2005).Google ScholarGoogle Scholar
  11. Hesse, S., Schulte-Tigges, G., Konrad, M., Bardeleben, A. and Werner, C. 2003. Robot-Assisted Arm Trainer for the Passive and Active Practice of Bilateral Forearm and Wrist Movements in Hemiparetic Subjects. Arch of Phys Med Rehabil, 84 (2003), 915--920.Google ScholarGoogle ScholarCross RefCross Ref
  12. Hesse, S., Werner, C., Pohl, M., Rueckriem, S., Mehrholz, J. and Lingnau, M. 2005. Computerized Arm Training Improves the Motor Control of the Severely Affected Arm After Stroke: A Single-Blinded Randomized Trial in Two Centers. J. of Stroke, 36 (2005), 1960--1966.Google ScholarGoogle ScholarCross RefCross Ref
  13. Reinkensmeyer, D., Kahn, L., Averbuch, M., McKenna-Cole, A., Schmit, B. and Rymer, W. Z. 2000. Understanding and treating arm movement after chronic brain injury: progress with the ARM Guide. J. of Rehabil Res Dev, 37, 6 (2000), 653--662.Google ScholarGoogle Scholar
  14. Kahn, L., Averbuch, M., Rymer, W. and Reinkensmeyer, D. 2001. Comparison of Robot-Assisted Reaching to Free Reaching in Promoting Recovery from Chronic Stroke. In Proceedings of ICORR (Evry, France, April 25--27, 2001).Google ScholarGoogle Scholar
  15. Patton, J. L., Kovic, M. and Mussa-Ivaldi, F. A. 2006. Custom-designed haptic training for restoring reaching ability to individuals with poststroke hemiparesis. J. of Rehabilitation Research and Development, 43, 5 (2006), 643--655.Google ScholarGoogle ScholarCross RefCross Ref
  16. Wei, Y., Bajaj, P., Scheidt, R. and Patton, J. L. 2005. A Real-Time Haptic/Graphic Demonstration of how Error Augmentation can Enhance Learning. In Proceedings of ICRA (Barcelona, Spain, April 18--22, 2005).Google ScholarGoogle Scholar
  17. Amirabdollahian, F., Loureiro, R., Driessen, B. and Harwin, W. 2001. Error Correction Movement for Machine Assisted Stroke Rehabilitation. In Proceedings of ICORR (Evry, France, April 25--27, 2001).Google ScholarGoogle Scholar
  18. Harwin, W., Loureiro, R., Amirabdollahian, F., Taylor, M., Johnson, G., Stokes, E., Coote, S., Topping, M., Collin, C. and Tamparis, S. 2001. The GENTLE/S Project: A New Method of Delivering Neuro-Rehabilitation. In Proceedings of AAATE (Ljubljana, Slovenia, 2001).Google ScholarGoogle Scholar
  19. Loureiro, R., Amirabdollahian, F., Topping, M., Driessen, B., and Harwin., W. 2003. Upper Limb Robot Mediated Stroke Therapy-GENTLE/s Approach. J. of Autonomous Robots, 15, 1 (2003), 35--51. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Amirabdollahian, F., Loureiro, R. and Harwin, W. 2002. Minimum Jerk Trajectory Control for Rehabilitation and Haptic Applications. In Proceedings of ICRA (Washington, DC, USA, May 11--15, 2002).Google ScholarGoogle Scholar
  21. Kwakkel, G., Kollen, B. and Krebs, H. 2008. Effects of Robot-Assisted Therapy on Upper Limb Recovery After Stroke: A Systematic Review. J. of Neurorehabil Neural Repair, 22, 2 (2008), 111--121.Google ScholarGoogle ScholarCross RefCross Ref
  22. Mehrholz, J., Platz, T., Kugler, J. and Pohl, M. 2009. Electromechanical and robot-assisted arm training for improving arm function and activities of daily living after stroke (Review). J. of Stroke, 40, 5 (2009).Google ScholarGoogle Scholar
  23. Prange, G., Jannink, M., Groothuis-Oudshoorn, C., Hermens, H. and IJzerman, M. 2006. Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. J. of Rehabil Res Dev, 43, 2 (2006), 171--184.Google ScholarGoogle ScholarCross RefCross Ref
  24. Kahn, L., P. Lum, Rymer, W. and Reinkensmeyer, D. 2006. Robot-assisted movement training for the stroke-impaired arm: Does it matter what the robot does? J. of Rehabil Res Dev, 43, 5 (2006), 619--630.Google ScholarGoogle ScholarCross RefCross Ref
  25. Coote, S., Stokes, E., Murphy, B. and Harwin, W. 2003. The effect of GENTLE/S robot-mediated therapy on upper extremity dysfunction post stroke. In Proceedings of ICORR (Daejeon, Republic of Korea, 2003).Google ScholarGoogle Scholar
  26. Amirabdollahian, F., Loureiro, R., Gradwell, E., Collin, C., Harwin, W. and Johnson., G. 2007. Multivariate Analysis of the Fugl-Meyer Outcome Measures Assessing the Effectiveness of the GENTLE/S Robot-Mediated Stroke Therapy. J. of NeuroEngg & Rehabil, 4, 4 (2007).Google ScholarGoogle Scholar
  27. Linde, R. V. d. and Lammertse, P. 2003. HapticMaster --a generic force controlled robot for human interaction. Industrial Robot: An International Journal, 30, 6 (2003), 515--524.Google ScholarGoogle ScholarCross RefCross Ref
  28. Goodrich, M. and Schultz, A. 2007. Human-Robot Interaction: A Survey. J. of Foundations and Trends in Human-Computer Interaction, 1, 3 (2007), 203--275. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  • Published in

    cover image ACM Other conferences
    AH '12: Proceedings of the 3rd Augmented Human International Conference
    March 2012
    162 pages
    ISBN:9781450310772
    DOI:10.1145/2160125

    Copyright © 2012 ACM

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    Publication History

    • Published: 8 March 2012

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