skip to main content
10.1145/3133793.3133810acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicbipConference Proceedingsconference-collections
research-article

Design and Evaluation of the Lower-limb Robotic Orthosis for Gait Rehabilitation Actuated by Pneumatic Artificial Muscle

Published:23 August 2017Publication History

ABSTRACT

In this study, a robotic orthosis for lower-limb rehabilitation training is developed. The robot includes two hip and knee joints. Each joint is actuated by a pneumatic artificial muscle (PAM) in an antagonistic configuration. The bi-articular muscles are used to increase the stiffness of robotic orthosis. The robotic orthosis is evaluated not only by comparing to the normal human walking but also in trajectory tracking control mode. The experiment results show that the angle trajectory of the robotic orthosis is closed to the trajectory of normal human walking and it can also guide the subject to it designated trajectory.

References

  1. Behrman, A. L., and Harkema, S. J. Locomotor training after human spinal cord injury: A series of case studies. Physical Therapy, 2000. 80(7), 688--700.Google ScholarGoogle Scholar
  2. Jezernik, S., Colombo, G., and Morari, M. Automatic gait-pattern adaptation algorithms for rehabilitation with a 4-DOF robotic orthosis. IEEE Transactions on Robotics and Automation, 2004. 20(3), 574--582. Google ScholarGoogle ScholarCross RefCross Ref
  3. Veneman, J. F., et al., Design and Evaluation of the LOPES Exoskeleton Robot for Interactive Gait Rehabilitation. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2007. 15(3), 379--386. Google ScholarGoogle ScholarCross RefCross Ref
  4. Asseldonk, E. H. F. v., et al. The Effects on Kinematics and Muscle Activity of Walking in a Robotic Gait Trainer During Zero-Force Control. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2008. 16(4), 360--370. Google ScholarGoogle ScholarCross RefCross Ref
  5. Hussain S., et al., Assist-as-Needed Control of an Intrinsically Compliant Robotic Gait Training Orthosis. IEEE Transactions on Industrial Electronics, 2017. 64(2), 1675--1685. Google ScholarGoogle ScholarCross RefCross Ref
  6. Hussain, S., Xie S. Q., and Jamwal, P. K. Control of a robotic orthosis for gait rehabilitation. Robotics and Autonomous Systems, 2013. 61(9), 911--919. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Hussain, S., Xie, S.,Q., and Jamwal, P. K. Adaptive Impedance Control of a Robotic Orthosis for Gait Rehabilitation. IEEE Transactions on Cybernetics, 2013. 43(3), 1025--1034. Google ScholarGoogle ScholarCross RefCross Ref
  8. Dzahir, M. A. M., Nobutomo, T., and Yamamoto, S. I. Development of body weight support gait training system using pneumatic McKibben actuators -Control of Lower Extremity Orthosis. in 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). 2013.Google ScholarGoogle ScholarCross RefCross Ref
  9. Shibata, Y., et al. Development of body weight support gait training system using antagonistic bi-articular muscle model. in 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology. 2010.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Design and Evaluation of the Lower-limb Robotic Orthosis for Gait Rehabilitation Actuated by Pneumatic Artificial Muscle

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Other conferences
      ICBIP '17: Proceedings of the 2nd International Conference on Biomedical Signal and Image Processing
      August 2017
      95 pages
      ISBN:9781450352680
      DOI:10.1145/3133793

      Copyright © 2017 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 23 August 2017

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article
      • Research
      • Refereed limited

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader