Virtual reality training system based on lower limb rehabilitation robot

  • Authors

    • Hongbo Wang
    • Musong Lin
    • Zhennan Lin
    • Xincheng Wang
    • Jianye Niu
    • Hongfei Yu
    • Lili Zhang
    • Luige Vladareanu
    2018-05-16
    https://doi.org/10.14419/ijet.v7i2.28.12892
  • rehabilitation robot, virtual reality, interact strategy, serious game.

  • Abstract

    This paper presents a virtual reality training system for the lower limb rehabilitation robot, which can simulate the bike riding and encourage patients to join in the recovery training through the built-in competitive game. The virtual reality training is a variable speed active training under the constraint trajectory, and it has adapting training posture function which can provide individual riding training track according to the legs length of patients. The movement synchronization between the robot and virtual model is achieved by interaction control strategy, and robot can change the training velocity based on the signal from feedback terrains in game. A serious game about bike match in forest was designed, and the user can select the training level as well as change perspective through the user interface. The training can be paused at any time, and the timer function could reflect the recovery of patient.

     

  • References

    1. [1] Feng Y.F., Wang H.B., Lu T.T., et al (2016), Teaching training method of a lower limb rehabilitation robot. Int. J. Adv. Robot Syst., Vol. 13, No. 2, pp. 1-11.

      [2] Ozkul F., Barkana D.E. (2013), Upper-extremity rehabilitation robot RehabRoby: methodology, design, usability and validation. Int. J. Adv. Robot Syst., Vol. 10, No. 1, pp. 1-13.

      [3] Wei W.Q., Hou Z.G., Cheng L., et al (2016), Toward patients’ motion intention recognition: dynamics modeling and identification of iLeg—an LLRR under Motion constraints. IEEE Transactions on Systems Man & Cybernetics Systems, Vol. 46, No. 7, pp. 980-992.

      [4] Fouad K., Krajacic A., Tetzlaff W (2011), Spinal cord injury and plasticity: opportunities and challenges. Brain Research Bulletin, Vol. 84, No. 4, pp. 337-342.

      [5] Behrman A.L., Harkema S.J. (2000), Locomotor training after human spinal cord injury: a series of case studies. Physical therapy, Vol. 80, No. 7, pp. 688-700.

      [6] Fouad K., Tetzlaff W. (2012), Rehabilitative training and plasticity following spinal cord injury. Experimental Neurology, Vol. 235, No. 1, pp. 91-99.

      [7] Saini S., Rambli D.R.A., Sulaiman S., et al (2012), A low-cost game framework for a home-based stroke rehabilitation system. International Conference on Computer & Information Science, Vol. 1, pp. 55-60.

      [8] Holden M.K. (2005), Virtual environments for motor rehabilitation: review. Cyberpsycholo. Behav., Vol. 8, No. 3, pp. 187-211.

      [9] Schönauer C., Pintaric T., Kaufmann H. (2011), Full body interaction for serious games in motor rehabilitation. Augm. Human Int. Conf., Vol. 2, pp. 1-8.

      [10] Krebs H., Celestino J., Williams D., et al (2004), 24 A Wrist Extension for MITMANUS. Advances in Rehabilitation Robotics, Vol. 306, pp. 377-390.

      [11] Loureiro R., Amirabdollahian F., Topping M., et al (2003), Upper Limb Robot Mediated Stroke Therapy — GENTLE/s Approach. Reading: Autonomous Robots, Vol. 15, No. 1, pp. 35-51.

      [12] Furusho J., Li C.Q., Yamaguchi Y. (2005), A 6-DOF rehabilitation machine for upper limbs including wrists using ER actuators. Mechatronics and Automation, 2005 IEEE International Conference IEEE, Vol. 2, pp. 1033-1038.

      [13] Wei W., Guo S., Zhang W., et al (2013), A novel VR-based upper limb rehabilitation robot system. ICME International Conference on Complex Medical Engineering IEEE, pp. 302-306.

      [14] Feng Y.F., Wang H.B., Lu, T.T., et al (2016), Teaching training method of a lower limb rehabilitation robot. International Journal of Advanced Robotic Systems, Vol. 13, No. 2, pp. 1-11.

  • Downloads

  • How to Cite

    Wang, H., Lin, M., Lin, Z., Wang, X., Niu, J., Yu, H., Zhang, L., & Vladareanu, L. (2018). Virtual reality training system based on lower limb rehabilitation robot. International Journal of Engineering & Technology, 7(2.28), 119-122. https://doi.org/10.14419/ijet.v7i2.28.12892

    Received date: 2018-05-16

    Accepted date: 2018-05-16

    Published date: 2018-05-16