0
Research Papers

Design, Modeling, and Control of a Portable Leg Rehabilitation System

[+] Author and Article Information
Khaled M. Goher

Faculty of Environment Society and Design,
Lincoln University,
Lincoln 7647, New Zealand
e-mail: khaled.goher@lincoln.ac.nz

Sulaiman O. Fadlallah

School of Engineering, Computer, and
Mathematical Sciences,
Auckland University of Technology,
Auckland 1142, New Zealand
e-mail: sulaiman.fadlallah@aut.ac.nz

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received August 18, 2016; final manuscript received January 17, 2017; published online May 12, 2017. Assoc. Editor: Dumitru I. Caruntu.

J. Dyn. Sys., Meas., Control 139(7), 071013 (May 12, 2017) (15 pages) Paper No: DS-16-1410; doi: 10.1115/1.4035815 History: Received August 18, 2016; Revised January 17, 2017

In this work, a novel design of a portable leg rehabilitation system (PLRS) is presented. The main purpose of this paper is to provide a portable system, which allows patients with lower-limb disabilities to perform leg and foot rehabilitation exercises anywhere without any embarrassment compared to other devices that lack the portability feature. The model of the system is identified by inverse kinematics and dynamics analysis. In kinematics analysis, the pattern of motion of both leg and foot holders for different modes of operation has been investigated. The system is modeled by applying Lagrangian dynamics approach. The mathematical model derived considers calf and foot masses and moment of inertias as important parameters. Therefore, a gait analysis study is conducted to calculate the required parameters to simulate the model. Proportional derivative (PD) controller and proportional-integral-derivative (PID) controller are applied to the model and compared. The PID controller optimized by hybrid spiral-dynamics bacteria-chemotaxis (HSDBC) algorithm provides the best response with a reasonable settling time and minimum overshot. The robustness of the HSDBC–PID controller is tested by applying disturbance force with various amplitudes. A setup is built for the system experimental validation where the system mathematical model is compare with the estimated model using system identification (SI) toolbox. A significant difference is observed between both models when applying the obtained HSDBC–PID controller for the mathematical model. The results of this experiment are used to update the controller parameters of the HSDBC-optimized PID.

Copyright © 2017 by ASME
Your Session has timed out. Please sign back in to continue.

References

Díaz, I. , Gil, J. J. , and Sánchez, E. , 2011, “ Lower-Limb Robotic Rehabilitation: Literature Review and Challenges,” J. Rob., 2011, p. 759764.
Monaco, V. , Galardi, G. , Coscia, M. , Martelli, D. , and Micera, S. , 2012, “ Design and Evaluation of NEUROBike: A Neurorehabilitative Platform for Bedridden Post-Stroke Patients,” IEEE Trans. Neural Syst. Rehabil. Eng., 20(6), pp. 845–852. [CrossRef] [PubMed]
Hwang, B. , and Jeon, D. , 2012, “ A Wheelchair Integrated Lower Limb Exercise/Rehabilitation System: Design and Experimental Results on the Knee Joint,” IEEE/SICE International Symposium on System Integration (SII), Fukuoka, Japan, Dec. 16–18, pp. 164–169.
Agrawal, S. K. , and Fattah, A. , 2004, “ Theory and Design of an Orthotic Device for Full or Partial Gravity-Balancing of a Human Leg During Motion,” IEEE Trans. Neural Syst. Rehabil. Eng., 12(2), pp. 157–165. [CrossRef] [PubMed]
Banala, S. K. , Agrawal, S. K. , Fattah, A. , Krishnamoorthy, V. , Hsu, W.-L. , Scholz, J. , and Rudolph, K. , 2006, “ Gravity-Balancing Leg Orthosis and Its Performance Evaluation,” IEEE Trans. Rob., 22(6), pp. 1228–1239. [CrossRef]
Agrawal, S. K. , Banala, S. K. , Fattah, A. , Sangwan, V. , Krishnamoorthy, V. , Scholz, J. P. , and Hsu, W.-L. , 2007, “ Assessment of Motion of a Swing Leg and Gait Rehabilitation With a Gravity Balancing Exoskeleton,” IEEE Trans. Neural Syst. Rehabil. Eng., 15(3), pp. 410–420. [CrossRef] [PubMed]
Banala, S. K. , Kim, S. H. , Agrawal, S. K. , and Scholz, J. P. , 2009, “ Robot Assisted Gait Training With Active Leg Exoskeleton (ALEX),” IEEE Trans. Neural Syst. Rehabil. Eng., 17(1), pp. 2–8. [CrossRef] [PubMed]
Banala, S. K. , Agrawal, S. K. , and Scholz, J. P. , 2010, “ Novel Gait Adaptation and Neuromotor Training Results Using an Active Leg Exoskeleton,” IEEE/ASME Trans. Mechatron., 15(2), pp. 216–225. [CrossRef]
Duschau-Wicke, A. , von Zitzewitz, J. , Caprez, A. , Lunenburger, L. , and Riener, R. , 2010, “ Path Control: A Method for Patient-Cooperative Robot-Aided Gait Rehabilitation,” IEEE Trans. Neural Syst. Rehabil. Eng., 18(1), pp. 38–48. [CrossRef] [PubMed]
Zhang, M. , and Li, X. , 2010, “ A Design of the Mechanism for Lower Limbs Passive Rehabilitation and Kinematics Analysis,” Fifth International Conference on Frontier of Computer Science and Technology (FCST), Changchun, China, Aug. 18–22, pp. 603–607.
Homma, K. , Fukuda, O. , and Nagata, Y. , 2002, “ Study of a Wire-Driven Leg Rehabilitation System,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Lausanne, Switzerland, Sept. 30–Oct. 4, pp. 1451–1456.
Homma, K. , Fukuda, O. , Sugawara, J. , Nagata, Y. , and Usuba, M. , 2003, “ A Wire-Driven Leg Rehabilitation System: Development of a 4-DOF Experimental System,” IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003), Kobe, Japan, July 20–24, Vol. 2, pp. 908–913.
Yakimovich, T. , Kofman, J. , and Lemaire, E. D. , 2006, “ Design and Evaluation of a Stance-Control Knee-Ankle-Foot Orthosis Knee Joint,” IEEE Trans. Neural Syst. Rehabil. Eng., 14(3), pp. 361–369. [CrossRef] [PubMed]
Park, Y.-L. , Chen, B. , Young, D. , Stirling, L. , Wood, R. J. , Goldfield, E. , and Nagpal, R. , 2011, “ Bio-Inspired Active Soft Orthotic Device for Ankle Foot Pathologies,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Francisco, CA, Sept. 25–30, pp. 4488–4495.
McNeal, D. R. , Nakai, R. J. , Meadows, P. , and Tu, W. , 1989, “ Open-Loop Control of the Freely-Swinging Paralyzed Leg,” IEEE Trans. Biomed. Eng., 36(9), pp. 895–905. [CrossRef] [PubMed]
Van Der Spek, J. H. , Velthuis, W. J. R. , Veltink, P. H. , and De Vries, T. J. A. , 1996, “ Neuro Fuzzy Control of the FES Assisted Freely Swinging Leg of Paraplegic Subjects,” 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Amsterdam, The Netherlands, Oct. 31–Nov. 3, pp. 2234–2235.
Tsukahara, A. , Hasegawa, Y. , and Sankai, Y. , 2011, “ Gait Support for Complete Spinal Cord Injury Patient by Synchronized Leg-Swing With HAL,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Francisco, CA, Sept. 25–30, pp. 1737–1742.
Aguirre-Ollinger, G. , Colgate, J. E. , Peshkin, M. , and Goswami, A. , 2012, “ Inertia Compensation Control of a One-Degree-of-Freedom Exoskeleton for Lower-Limb Assistance: Initial Experiments,” IEEE Trans. Neural Syst. Rehabil. Eng., 20(1), pp. 68–77. [CrossRef] [PubMed]
Vaughan, C. , Davis, B. , and O'Connor, J. , 1999, Dynamics of Human Gait, Kiboho Publishers, Cape Town, South Africa.
Tamura, K. , and Yasuda, K. , 2011, “ Spiral Dynamics Inspired Optimization,” J. Adv. Comput. Intell. Intell. Inf., 15(8), pp. 2–3.
Korani, W. M. , Dorrah, H. T. , and Emara, H. M. , 2008, “ Bacterial Foraging Oriented by Particle Swarm Optimization Strategy for PID Tuning,” GECCO Conference Companion on Genetic and Evolutionary Computation—GECCO’08, Atlanta, GA, July 12–16, p. 1823.
Nasir, A. N. K. , Tokhi, M. O. , Abd Ghani, N. M. , and Ahmad, M. A. , 2012, “ A Novel Hybrid Spiral Dynamics Bacterial-Foraging Algorithm for Global Optimization With Application to Control Design,” 12th Annual Workshop on Computational Intelligence (UKCI2012), Edinburgh, UK, Sept. 5–7, pp. 1–7.
Nasir, A. N. K. , Tokhi, M. O. , Abd Ghani, N. M. , and Ahmad, M. A. , 2012, “ A Novel Hybrid Spiral Dynamics Bacterial-Chemotaxis Algorithm for Global Optimization With Application to Controller Design,” UKACC International Conference on Control, Cardiff, UK, Sept. 3–5, pp. 753–758.
Nasir, A. N. K. , and Tokhi, M. O. , 2013, “ A Novel Hybrid Bacteria-Chemotaxis Spiral-Dynamics Algorithm With Application to Modelling of a Flexible System,” Fifth International Conference on Modeling, Simulation and Applied Optimization (ICMSAO’13), Hammamet, Tunisia, Apr. 28–30.

Figures

Grahic Jump Location
Fig. 4

Knee and ankle joint displacement–torque relation in adams

Grahic Jump Location
Fig. 3

Modes of operation

Grahic Jump Location
Fig. 2

System schematics diagram

Grahic Jump Location
Fig. 1

System overall design using solidworks

Grahic Jump Location
Fig. 9

Hybrid spiral-dynamics bacteria-chemotaxis (HSDBC) optimization algorithm

Grahic Jump Location
Fig. 6

PLRS schematic description of the control strategy

Grahic Jump Location
Fig. 7

Calf and foot system response using proportional derivative (PD) controller

Grahic Jump Location
Fig. 8

Calf and foot system response using PID controller

Grahic Jump Location
Fig. 5

(a) System open-loop response: angular positions with a unit step input and (b) system open-loop response: angular positions for a step input with a gain of 100

Grahic Jump Location
Fig. 18

Hardware low-pass filter

Grahic Jump Location
Fig. 17

Designed circuit for motor orientation control

Grahic Jump Location
Fig. 15

System identification toolbox graphical user interface (GUI)

Grahic Jump Location
Fig. 21

Calf and foot measured outputs

Grahic Jump Location
Fig. 10

Calf and foot system response comparison (manual tuning versus HSDBC)

Grahic Jump Location
Fig. 11

Characteristics parameters of calf and foot movement

Grahic Jump Location
Fig. 12

Calf and foot control effort comparison

Grahic Jump Location
Fig. 13

Disturbance signals applied on the system

Grahic Jump Location
Fig. 14

Calf and foot system response with external disturbance

Grahic Jump Location
Fig. 20

Prototype modes of operation

Grahic Jump Location
Fig. 23

Calf measured and simulated model output comparison

Grahic Jump Location
Fig. 24

Comparison between mathematical model and actual prototype by applying HSDBC–PID controller for calf

Grahic Jump Location
Fig. 25

Angular calf displacement (math. model HSDBC–PID controller versus updated HSDBC–PID controller)

Grahic Jump Location
Fig. 26

Foot measured and simulated model output comparison

Grahic Jump Location
Fig. 22

System behavior while input variation

Grahic Jump Location
Fig. 27

Comparison between mathematical model and actual prototype by applying HSDBC–PID controller for foot

Grahic Jump Location
Fig. 28

Angular foot displacement (math. model HSDBC–PID controller versus updated HSDBC–PID controller

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In