Advertisement

Virtual Reality Integration with Force Feedback in Upper Limb Rehabilitation

  • Víctor H. AndaluzEmail author
  • Pablo J. Salazar
  • Miguel Escudero V.
  • Carlos Bustamante D.
  • Marcelo Silva S.
  • Washington Quevedo
  • Jorge S. Sánchez
  • Edison G. Espinosa
  • David Rivas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10073)

Abstract

In this article, it presents an alternative rehabilitation system for upper extremity fine motor skills by using haptic devices implemented in a virtual reality interface. The proposed rehabilitation system develops 3D shapes and textures observed in virtual reality environments, interaction with environments generate specific rehabilitation exercises for conditions in patients to treat their conditions in the upper extremities; the system presents different rehabilitation environments focused on the use of virtual reality. The system is implemented through bilateral Unity3D software interaction with the Novint Falcon device further Oculus Rift and Leap motion is used for total immersion of the patient with the development of virtual reality. The patient performs a path, based in a rehabilitation entertainment brought about by the displacement and force feedback paths, which are based on physiotherapist’s exercises. Developed experimental results show the efficiency of the system, which generates the human interaction-machine, oriented to develop the human ability.

Keywords

Unity3D System rehabilitation Force feedback Virtual reality 

Notes

Acknowledgment

The authors would like to thanks to the Consorcio Ecuatoriano para el Desarrollo de Internet Avanzado -CEDIA- for financing the project “Tele-Operación Bilateral Cooperativo de Múltiples Manipuladores Móviles – CEPRAIX-2015-05”, and the Universidad de las Fuerzas Armadas ESPE for the technical and human support to develop this paper.

References

  1. 1.
    Ramírez-Fernández, C., Morán, A.L., García-Canseco, E.: Haptic feedback in motor hand virtual therapy increases precision and generates less mental workload. In: 2015 9th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), Istanbul, pp. 280–286 (2015)Google Scholar
  2. 2.
    Ramírez-Fernández, C., García-Canseco, E., Morán, A.L., Orihuela-Espina, F.: Design principles for hapto-virtual rehabilitation environments: effects on effectiveness of fine motor hand therapy. In: Fardoun, H.M., Penichet, V.M.R., Alghazzawi, D.M. (eds.) REHAB 2014. CCIS, vol. 515, pp. 270–284. Springer, Heidelberg (2015). doi: 10.1007/978-3-662-48645-0_23 CrossRefGoogle Scholar
  3. 3.
    Contu, S., Hughes, C., Masia, L.: Influence of visual information on bimanual haptic manipulation. In: 2015 IEEE International Conference on Rehabilitation Robotics (ICORR), Singapore, pp. 961–966 (2015)Google Scholar
  4. 4.
    Song, Z., Guo, S., Yazid, M.: Development of a potential system for upper limb rehabilitation training based on virtual reality. In: 2011 4th International Conference on Human System Interactions (HSI), Yokohama, pp. 352–356 (2011)Google Scholar
  5. 5.
    Ferre, M., Galiana, I., Wirz, R., Tuttle, N.: Haptic device for capturing and simulating hand manipulation rehabilitation. IEEE/ASME Trans. Mechatron. 16(5), 808–815 (2011)CrossRefGoogle Scholar
  6. 6.
    Zepeda-Ruelas, E., Gudiño-Lau, J., Durán-Fonseca, M., Charre-Ibarra, S., Alcalá-Rodríguez, J.: Control Háptico con Planificación de Trayectorias Aplicado a Novint Falcon. La Mecatrónica en México, vol. 3, no. 2, pp. 65–74, Mayo 2014Google Scholar
  7. 7.
    Haarth, R., Ejarque, G.E., Distefano, M.: INTERFAZ HÁPTICO APLICADA EN LA MANIPULACIÓN DE OBJETOS. Instituto de Automática y Electrónica Industrial, Facultad de Ingeniería Universidad Nacional de Cuyo (2010)Google Scholar
  8. 8.
    Hamza-Lup, F.G., Baird, W.H.: Feel the static and kinetic friction. In: Isokoski, P., Springare, J. (eds.) EuroHaptics 2012. LNCS, vol. 7282, pp. 181–192. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-31401-8_17 CrossRefGoogle Scholar
  9. 9.
    Tavakoli, M., Patel, R.V., Moallem, M.: Haptic interaction in robot-assisted endoscopic surgery: a sensorized end-effector, 15 January 2005Google Scholar
  10. 10.
    Gupta, A., O’Malley, M.K.: Design of a haptic arm exoskeleton for training and rehabilitation. Trans. Mechatron IEEE/ASME 11(3), 280–289 (2006)CrossRefGoogle Scholar
  11. 11.
    Anani, A.B., Waldemark, J., Hagert, C.G., Nyström, Å.: Muscle strength measurement in the hand as a diagnostic method for nerve injury a pilot study. In: 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Paris, France (1992)Google Scholar
  12. 12.
    Khor, K.X., Chin, P.J.H., Hisyam, A.R., Yeong, C.F., Narayanan, A.L.T., Su, E.L.M.: Development of CR2-haptic: a compact and portable rehabilitation robot for wrist and forearm training. In: IEEE Conference on Biomedical Engineering and Sciences (IECBES), Kuala Lumpur (2014)Google Scholar
  13. 13.
    Renon, P., Yang, C., Ma H., Cui R.: Haptic interaction between human and virtual iCub robot using Novint Falcon with CHAI3D and MATLAB. In: 32nd Chinese Control Conference (CCC), Xi’an, pp. 6045–6050 (2013)Google Scholar
  14. 14.
    D’Auria, D., Persia, F., Siciliano, B.: A low-cost haptic system for wrist rehabilitation. In: 2015 IEEE International Conference on Information Reuse and Integration (IRI), San Francisco, CA, pp. 491–495 (2015)Google Scholar
  15. 15.
    Wang, C., et al.: Development of a rehabilitation robot for hand and wrist rehabilitation training. In: 2015 IEEE International Conference on Information and Automation, Lijiang, pp. 106–111 (2015)Google Scholar
  16. 16.
    Spencer, S.J., Klein, J., Minakata, K., Le, V., Bobrow, J.E., Reinkensmeyer, D.J.: A low cost parallel robot and trajectory optimization method for wrist and forearm rehabilitation using the Wii. In: 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics, Scottsdale, AZ, pp. 869–874 (2008)Google Scholar
  17. 17.
    Barbosa, A.M., Rodrigues, L.A.O., dos Santos, S.S., Gonçalves, R.S.: Comparison of a mechanical and biomechanical system applied in the human wrist rehabilitation using a cable-based system. In: Robotics Symposium and Latin American Robotics Symposium (SBR-LARS), Brazilian, Fortaleza, pp. 120–124 (2012)Google Scholar
  18. 18.
    Adamovich, S., et al.: A virtual reality–based exercise system for hand rehabilitation post-stroke. Teleoperators Virtual Environ. 14, 161–174 (2005)CrossRefGoogle Scholar
  19. 19.
    Turolla, A., Dam, M., Ventura, L., Tonin, P., Agostini, M., Zucconi, C., Piron, L.: Virtual reality for the rehabilitation of the upper limb motor function after stroke: a prospective controlled trial. J. Neuroeng. Rehabil. 10(1), 1 (2013)CrossRefGoogle Scholar
  20. 20.
    Szmeková, L., Havelková, J., Katolicka, T.: The efficiency of cognitive therapy using virtual reality on upper limb mobility in stroke patients. In: 2015 International Conference on Virtual Rehabilitation Proceedings (ICVR), pp. 115–116. IEEE, June 2015Google Scholar
  21. 21.
    Sen, S., Xiang, Y., Ming, E., Xiang, K., Fai, Y., Khan, Q.: Enhancing effectiveness of virtual reality rehabilitation system: Durian Runtuh. In: 2015 10th Asian Control Conference (ASCC), pp. 1–6. IEEE, May 2015Google Scholar
  22. 22.
    Andaluz, V.H., Salazar, P.J., Silva M.S., Escudero, M., Bustamante C.D.: Rehabilitation of upper limb with force feedback. IEEE International Conference on Automatica ICA/ACCA 2016, vol. 22, Curicó, Chile, 19–21 de October 2016, in pressGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Víctor H. Andaluz
    • 1
    Email author
  • Pablo J. Salazar
    • 1
  • Miguel Escudero V.
    • 1
  • Carlos Bustamante D.
    • 1
  • Marcelo Silva S.
    • 1
  • Washington Quevedo
    • 1
  • Jorge S. Sánchez
    • 1
  • Edison G. Espinosa
    • 1
  • David Rivas
    • 1
  1. 1.Universidad de las Fuerzas Armadas ESPESangolquíEcuador

Personalised recommendations