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A 3-PRS parallel manipulator for ankle rehabilitation: towards a low-cost robotic rehabilitation

Published online by Cambridge University Press:  13 March 2015

Marina Vallés
Affiliation:
Departamento de Ingeniería de Sistemas y Automática, Universidad Politécnica de Valencia, Valencia 46022, Spain (e-mail: [email protected], [email protected]).
José Cazalilla
Affiliation:
Departamento de Ingeniería de Sistemas y Automática, Universidad Politécnica de Valencia, Valencia 46022, Spain (e-mail: [email protected], [email protected]).
Ángel Valera*
Affiliation:
Departamento de Ingeniería de Sistemas y Automática, Universidad Politécnica de Valencia, Valencia 46022, Spain (e-mail: [email protected], [email protected]).
Vicente Mata
Affiliation:
Centro de Investigación de Tecnología de Vehículos, Universidad Politécnica de Valencia, Valencia 46022, Spain (e-mail: [email protected]).
Álvaro Page
Affiliation:
Departamento de Física Aplicada, Universidad Politécnica de Valencia, Valencia 46022, Spain (e-mail: [email protected]).
Miguel Díaz-Rodríguez
Affiliation:
Departamento de Tecnología y Diseño, Facultad de Ingeniería, Universidad de los Andes, Mérida 5101, Venezuela (e-mail: [email protected]).
*
*Corresponding author. E-mail: [email protected]

Summary

This paper presents the design, kinematics, dynamics and control of a low-cost parallel rehabilitation robot developed at the Universitat Politècnica de Valencia. Several position and force controllers have been tested to ensure accurate tracking performances. An orthopedic boot, equipped with a force sensor, has been placed over the platform of the parallel robot to perform exercises for injured ankles. Passive, active-assistive and active-resistive exercises have been implemented to train dorsi/plantar flexion, inversion and eversion ankle movements. In order to implement the controllers, the component-based middleware Orocos has been used with the advantage over other solutions that the whole scheme control can be implemented modularly. These modules are independent and can be configured and reconfigured in both configuration and runtime. This means that no specific knowledge is needed by medical staff, for example, to carry out rehabilitation exercises using this low-cost parallel robot. The integration between Orocos and ROS, with a CAD model displaying the actual position of the rehabilitation robot in real time, makes it possible to develop a teleoperation application. In addition, a teleoperated rehabilitation exercise can be performed by a specialist using a Wiimote (or any other Bluetooth device).

Type
Articles
Copyright
Copyright © Cambridge University Press 2015 

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References

1. Patel, Y. D. and George, P. M., “Parallel manipulators applications–-a survey,” Mod. Mech. Eng. 2, 5764 (2012).CrossRefGoogle Scholar
2. Pisla, D., Gherman, B., Vaida, C., Suciu, M. and Plitea, N., “An active hybrid parallel robot for minimally invasivesurgery,” Robot. Comput.-Integr. Manuf. 29, 203221 (2013).Google Scholar
3. Díaz, I., Gil, J. and Sánchez, E., “Lower-limb robotic rehabilitation: Literature review and challenges,” J. Robot. 2011, Article ID 759764, 111 (2011).CrossRefGoogle Scholar
4. del-Ama, A., Koutsou, A. and Moreno, J., “Review of hybrid exoskeletons to restore gait following spinal cord injury,” J. Rehabil. Res. Dev. 49 (4), 497514 (2012).CrossRefGoogle ScholarPubMed
5. Colombo, G., Joerg, M. and Schreier, R., “Treadmill training of paraplegic patients using a robotic orthosis,” J. Rehabil. Res. Dev. 37 (6), 693700 (2000).Google Scholar
6. Hesse, S. and Uhlenbrock, D., “A mechanized gait trainer for restoration of gait,” J. Rehabil. Res. Dev. 37 (6), 701708 (2000).Google Scholar
7. Peshkin, M., Brown, D. and Santos-Munné, J., “KineAssist: A Robotic Overground Gait and Balance Training Device,” Proceedings of the 9th IEEE International Conference on Rehabilitation Robotics, (ICORR '05), Evanston, Ill, USA (Jul. 2005) pp. 241–246.Google Scholar
8. Schmitt, C., Métrailler, P. and Al-Khodairy, A., “The Motion Maker: A Rehabilitation System Combining an Orthosis with Closed-Loop Electrical Muscle Stimulation,” Proceedings of the 8th Vienna International Workshop on Functional Electrical Stimulation, Vienna, Austria (Sep. 2004) pp. 117–120.Google Scholar
9. van Delden, A., Peper, C. and Kwakkel, G., “A systematic review of bilateral upper limb training devices for poststroke rehabilitation,” Stroke Res., Treat. Article 972069 (2012) pp. 117.Google Scholar
10. Bharadwaj, K. and Sugar, T., “Kinematics of a Robotic Gait Trainer for Stroke Rehabilitation,” Proceedings of the IEEE International Conference on Robotics and Automation, (ICRA '06), Orlando, Fla, USA (May 2006) pp. 3492–3497.Google Scholar
11. Prange, G. and Jannink, M., “Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke,” J. Rehabil. Res. Dev. 43 (2), 171184 (2006).Google Scholar
12. Rocon, E., Belda-Lois, J. and Ruiz, A., “Design and validation of a rehabilitation robotic exoskeleton for tremor assessment and suppression,” IEEE Trans. Neural Syst. Rehabil. Eng. 15 (3), 367378 (2007).Google Scholar
13. Saglia, J., Tsagarakis, N., Dai, J. and Caldwell, D., “Control strategies for patient-assisted training using the ankle rehabilitation robot (ARBOT),” IEEE/ASME Trans. Mechatronics 99, 110 (2012).Google Scholar
14. Tsoi, Y., Xie, S. and Graham, A., “Design, modeling and control of an ankle rehabilitation robot,” Des. Control Intell. Robot. Syst., vol. 177, 377399 (2012).Google Scholar
15. Syrseloudis, C. and Emiris, I., “Design framework for a simple robotic ankle evaluation and rehabilitation device,” 30th Annual International IEEE EMBS Conference, Vancouver (Aug. 2008) pp. 4310–4313.CrossRefGoogle Scholar
16. Dai, J., Zhao, T. and Nester, C., “Sprained ankle physiotherapy based mechanism synthesis and stiffness analysis of a robotic rehabilitation device,” Auton. Robots 16, 207218 (2004).Google Scholar
17. Yoon, J., Ryu, J. and Lim, K., “Reconfigurable ankle rehabilitation robot for various exercises,” J. Robot. Syst. 11 1533 (2006).Google Scholar
18. Girone, M., Burdea, G. and Bouzit, M., “The Rutgers Ankle Orthopedic Rehabilitation Interface,” Proceedings of the ASME International Mechanical Enge. Congr. Dyn. Syst. Control Div., Nashville, TN (Nov. 1999) vol. 67, pp. 305–312.Google Scholar
19. Syrseloudis, C. and Emiris, I., “A Parallel Robot for Ankle Rehabilitation-Evaluation and its Design Specifications,” Proceedings of IEEE BioInformatics and BioEngineering (2008) pp. 1–6.Google Scholar
20. Fan, Y. and Yin, Y., “Mechanism Design and Motion Control of a Parallel Ankle Joint for Rehabilitation Robotic Exoskeleton,” Proceedings of IEEE Robotics and Biomimetics, China (2009) pp. 2527–2532.Google Scholar
21. Wang, C., Yuefa, F., Sheng, G. and Chagchum, Z., “Design and kinematic analysis of redundantly actuated parallel mechanisms for ankle rehabilitation,” Robotica 119 (2014).Google Scholar
22. Patane, F. and Cappa, P., “A 3-DOF parallel robot with spherical motion for the rehabilitation and evaluation of balance performance,” IEEE Trans. Neural Syst. Rehabil. Eng. 19 (2), (2011) pp. 157166.CrossRefGoogle ScholarPubMed
23. Vallés, M., Díaz-Rodríguez, M., Valera, Á., Mata, V., and Page, Á., “Mechatronic development and dynamic control of a 3-DOF parallel manipulator,” Mech. Based Des. Struct. Mach. 40 (4), 434452 (2012).CrossRefGoogle Scholar
24. de Jalon, J. and Bayo, E., Kinematic and Dynamic Simulation of Multibody Systems: The Real-Time Challenge (Springer-Verlag, New-York, 1994).Google Scholar
25. Li, Y. and Xu, Q., “Kinematic analysis of a 3-PRS parallel manipulator,” Robot. Comput.-Integr. Manuf. 23 (4), 395408 (2007).Google Scholar
26. Khalil, W. and Dombre, E., Modeling, Identification and Control of Robots. (London, Hermes Penton, 2002).Google Scholar
27. Díaz-Rodríguez, M., Mata, V., Valera, Á. and Page, Á., “A methodology for dynamic parameters identification of 3-DOF parallel robots in terms of relevant parameters,” Mech. Mach. 45 13371356 (2010).CrossRefGoogle Scholar
28. Ortega, R. and Spong, M., “Adaptive motion control of rigid robots: A tutorial,” Autom. 25 (6), 877888 (1989).CrossRefGoogle Scholar
29. Paden, B. and Panja, R., “Globally asymptotically stable PD+ controller for robot manipulators,” Int. J. Control 47 (6), 16971712 (1988).Google Scholar
30. Slotine, J. J. E. and Li, W., “On the adaptive control of robot manipulators,” Int. J. Robot. Res. 6, 4959 (1987).CrossRefGoogle Scholar
31. Sadegh, N. and Horowitz, N. R., “Stability and robustness analysis of a class of adaptative controllers for robotics manipulators,” Int. J. Robot. Res. 9, 7494 (1990).Google Scholar
32. Volpe, R. and Khosla, P., “A theoretical and experimental investigation of explicit force control strategies for manipulators,” IEEE Trans. Autom. Control 38 (11), 16341650 (1993).Google Scholar
33. Aström, K. and Murray, R., Feedback Systems: An Introduction for Scientists and Engineers. Princeton University Press (2010).Google Scholar
34. Siciliano, B. and Villani, L., Robot Force Control (Kluwer Academic Publishers, Norwell, MA, USA, 2000, ISBN: 0792377338).Google Scholar
35. Hogan, N., “Impedance control: An approach to manipulation: Part illapplications,” J. Dyn. Syst. Meas. Control 107 (2) 1724 (1985).Google Scholar
36. Sciavicco, L. and Siciliano, B., Modelling and Control of Robot Manipulators. (Mc Graw Hill, London, 2000).CrossRefGoogle Scholar
37. Lu, Z. and Goldenberg, A. A., “Robust impedance control and force regulation: Theory and experiments,” Int. J. Robot. Res. 14 (3), 225254 (1995).Google Scholar
38. Bruyninckx, H., “Open robot control software: The OROCOS project,” Available at: http://www.orocos.org. 2013.Google Scholar
39. Alonso, D., Pastor, J., Sánchez, P., and Álvarez, B., “Generación automática de software para sistemas de tiempo real: Un enfoque basado en componentes, modelos y frameworks,” Rev. Iberoamericana de Autom. e Inform. Ind. 9 (2), 170181 (2012).CrossRefGoogle Scholar
40. Quigley, M., Conley, K. and Gerkey, B., “ROS: An Open-Source Robot Operating System,” In ICRA Workshop on Open Source Software, vol. 3, no. 3.2. (2009).Google Scholar
41. Siegler, S., Chen, J. and Schneck, C., “The three-dimensional kinematics and flexibility characteristics of the human ankle and subtalar joints–part I: Kinematics,” J. Biomech. 110 (4) 364373 (1988).Google Scholar
42. Dettwyler, M., Stacoff, A. and Quervain, I. K., “Modelling of the ankle joint complex. Reflections with regards to ankle prostheses,” Foot Ankle Surg. 10 (3), 109119 (2004).CrossRefGoogle Scholar
43. Safran, M., Benedetti, R. and Bartolozzi, A., “Lateral ankle sprains: A comprehensive review: part 1: etiology, pathoanatomy, histopathogenesis, and diagnosis,” Med. Sci. 31 (7), 429437 (1999).Google Scholar
44. Smits, R. and Bruyninckx, H., “Composition of complex robot applications via data flow integration,” IEEE Int. Conf. Robotics and Automation (ICRA), Shanghai, China (2011) pp. 5576–5580.Google Scholar