The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
권호 표지
DOI QR코드

DOI QR Code

Control Algorithm of a Wearable Walking Robot for a Patient with Hemiplegia

편마비 환자를 위한 착용형 보행 로봇 제어 알고리즘 개발

  • Received : 2020.08.13
  • Accepted : 2020.11.06
  • Published : 2020.11.30
Download PDF
⟨ Previous Next ⟩

Abstract

This paper presents a control algorithm for a wearable walking aid robot for subjects with paraplegia after stroke. After a stroke, a slow, asymmetrical and unstable gait pattern is observed in a number of patients. In many cases, one leg can move in a relatively normal pattern, while the other leg is dysfunctional due to paralysis. We have adopted the so-called assist-as-needed control that encourages the patient to walk as much as possible while the robot assists as necessary to create the gait motion of the paralyzed leg. A virtual wall was implemented for the assist-as-needed control. A position based admittance controller was applied in the swing phase to follow human intentions for both the normal and paralyzed legs. A position controller was applied in the stance phase for both legs. A power controller was applied to obtain stable performance in that the output power of the system was delimited during the sample interval. In order to verify the proposed control algorithm, we performed a simulation with 1-DOF leg models. The preliminary results have shown that the control algorithm can follow human intentions during the swing phase by providing as much assistance as needed. In addition, the virtual wall effectively guided the paralyzed leg with stable force display.

Keywords

References

  1. B. Hobbs and P. Artemiadis, "A Review of Robot-Assisted Lower-Limb Stroke Therapy: Unexplored Paths and Future Directions in Gait Rehabilitation," Frontiers in Neurorobotics, Apr., 2020, DOI: 10.3389/fnbot.2020.00019.
  2. S. K. Banala, S. H. Kim, S. K. Agrawal, and J. P. Scholz, "Robot Assisted Gait Training With Active Leg Exoskeleton (ALEX)," IEEE Trans. on Neural Systems and Rehabilitation Engineering, vol. 17, no. 1, pp. 2-8, Feb., 2009, DOI: 10.1109/TNSRE.2008.2008280.
  3. S. Srivastava, P.-C. Kao, S. H. Kim, P. Stegall, D. Zanotto, J. S. Higginson, S. K. Agrawal, and J. P. Scholz, "Assist-as-Needed Robot-Aided Gait Training Improves Walking Function in Individuals Following Stroke," IEEE Trans. on Neural Systems and Rehabilitation Engineering, vol. 23, no. 6, pp. 956-963, Nov., 2015. DOI: 10.1109/TNSRE.2014.2360822.
  4. Hocoma, https://www.hocoma.com, Accessed: Oct. 11, 2020.
  5. C. Chen, S. Zhang, X. Zhu, J. Shen, and Z. Xu, "Disturbance Observer-Based Patient-Cooperative Control of a Lower Extremity Rehabilitation Exoskeleton," Int. J. of Precision Engineering and Manufacturing, vol. 21, pp. 957-968, Jan., 2020, DOI: 10.1007/s12541-019-00312-9.
  6. A. C. Villa-Parra, J. Lima, D. Delisle-Rodriguez, L. VargasValencia, A. Frizera-Neto, and T. Bastos, "Assessment of an Assistive Control Approach Applied in an Active Knee Orthosis Plus Walker for Post-Stroke Gait Rehabilitation," Sensors, vol. 20, Apr., 2020, DOI: 10.3390/s20092452.
  7. G. Huang, W. Zhang, F. Meng, Z. Yu, X. Chen, M. Ceccarelli, and Q. Huang, "Master-slave control of an intention-actuated exoskeletal robot for locomotion and lower extremity rehabilitation," Int. J. of Precision Engineering and Manufacturing, vol. 19, no. 7, pp. 983-991, Aug., 2018, DOI: 10.1007/s12541-018-0116-x.
  8. K.-H. Kim, "Mechanism and Control of the Wearable Walking Robot," 2019 Conference on Information and Control Symposium, Kyung-ju, Korea, pp. 143-144, Oct. 2019.
  9. A. Kaelin-Lang, L. Sawaki, and L. G. Cohen, "Role of voluntary drive in encoding an elementary motor memory," J. Neurophysiology, vol. 93, no. 2, pp. 1099-1103, Mar., 2005, DOI: 10.1152/jn.00143.2004.
  10. M. Lotze, C. Braun, N. Birbaumer, S. Anders, and L. G. Cohen, "Motor learning elicited by voluntary drive," Brain, vol. 126, no. 4, pp. 866-872, Apr., 2003, DOI: 10.1093/brain/awg079.
  11. R. Riener, L. Lunenburger, S. Jezernik, M. Anderschitz, G. Colombo, and V. Dietz, "Patient-Cooperative Strategies for Robot-Aided Treadmill Training: First Experimental Results," IEEE Trans. On Neural Systems and Rehabilitation Engineering, vol. 13, no. 3, pp. 380-494, Sept., 2005, DOI: 10.1109/TNSRE.2005.848628.
  12. A. Duschau-Wicke, J. von Zitzewitz, A. Caprez, L. Lunenburger, and R. Riener, "Path Control: A Method for Patient-Cooperative Robot-Aided Gait Rehabilitation," IEEE Trans. On Neural Systems and Rehabilitation Engineering, vol. 18, no. 1, pp. 38-48, Feb., 2010, DOI: 10.1109/TNSRE.2009.2033061.
  13. A. Q. Keemink, H. van der Kooij and A. HA Stienen, "Admittance control for physical human-robot interaction," Int. J. Robotics Research, vol. 37, no. 11, pp. 1421-1444, Apr., 2018, DOI: 10.1177/0278364918768950.
  14. C. Ott, R. Mukherjee, and Y. Nakamura, "Unified Impedance and Admittance Control," 2010 IEEE International Conference on Robotics and Automation, Anchorage, AK, USA, pp. 554-561, 2010, DOI: 10.1109/ROBOT.2010.5509861.
  15. A. Wahrburg and K. Listmann, "MPC-based Admittance Control for Robotic Manipulators," 2016 IEEE 55th Conference on Decision and Control (CDC), Las Vegas, NV, USA, pp. 7548-7554, Dec., 2016, DOI: 10.1109/CDC.2016.7799435.
  16. B. Hannaford and J.-H. Ryu, "Time-domain passivity control of haptic interfaces," IEEE Trans. Robot. Automat., vol. 18, no. 1, pp. 1-10, Feb., 2002, DOI: 10.1109/70.988969.
  17. S. Stramigioli, C. Secchi, A. J. van der Schaft, and C. Fantuzzi, "Sampled data systems passivity and discrete port-hamiltonian systems," IEEE Trans. on Robotics, vol. 21, no. 4, pp. 574-587, Aug., 2005, DOI: 10.1109/TRO.2004.842330.
  18. Colgate, J. E., "The Control of Dynamically Interacting Systems," PhD dissertation, MIT, Cambridge, USA, 1988, [Online], http://hdl.handle.net/1721.1/14380.