3D Virtual System Trough 3 Space Mocap Sensors for Lower Limb Rehabilitation

  • Edwin PrunaEmail author
  • Marco Pilatásig
  • Hamilton Angueta
  • Christian Hernandez
  • Ivón Escobar
  • Eddie D. Galarza
  • Nancy Jacho
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10325)


A 3D virtual system is presented for rehabilitation of lower limbs trough 3 Space Mocap Sensors and the Unity 3D environment, also, two games are designed to allow the flexion, extension and strengthening movements. The games have some difficulty levels thought for every rehabilitation stage. The system was used by 4 people with knee problems, which completed the whole exercise. In addition the participants performed a SEQ usability test with results of (53 ± 0,56), this shows that the systems has a good acceptation to be used for rehabilitation.


3 Space Mocap Unity 3D Rehabilitation SEQ 



We thank the “Universidad de las Fuerzas Armadas ESPE” for financing the investigation project number 2015-PIC-006.


  1. 1.
    Li, D., Tan, Z., Kang, P., Shen, B., Pei, F.: Effects of multi-site infiltration analgesia on pain management and early rehabilitation compared with femoral nerve or adductor canal block for patients undergoing total knee arthroplasty: a prospective randomized controlled trial Int. Orthop. 41(1), 75–83 (2017)Google Scholar
  2. 2.
    Van Baar, M.E., Dekker, J., Oostendorp, R., Bijl, D., Voorn, T.B., Bijlsma, J.W.J.: Effectiveness of exercise in patients with osteoarthritis of hip or knee: nine months’ follow up. Ann. Rheum. Dis. 60(12), 1123–1130 (2001)CrossRefGoogle Scholar
  3. 3.
    Gonzalez, A., Fraisse, P., Hayashibe, M.: Adaptive interface for personalized center of mass self-identification in home rehabilitation. IEEE Sensors J. 15(5), 2814–2823 (2015)Google Scholar
  4. 4.
    Ferreira dos Santos, L., Christ, O., Mate, K., Schmidt, H., Krüger, J., Dohle, C.: Movement visualisation in virtual reality rehabilitation of the lower limb: a systematic review. Biomed. Eng. 15 (2016). Art. no. 144Google Scholar
  5. 5.
    Valvoda, J.T.: Virtual humanoids and presence in virtual environments. Ph.D. thesis. Rheinisch-Westfälische Technische Hochschule Aachen, Fakultät für Mathematik, Informatik und Naturwissenschaften (2007)Google Scholar
  6. 6.
    Schüler, T., Ferreira dos Santos, L., Hoermann, S.: Harnessing the experience of presence for virtual motor rehabilitation: towards a guideline for the development of virtual reality environments. In: Sharkey, P.M., Pareto, L., Broeren, J., Rydmark, M. (eds.) Proceedings of the 10th International Conference on Disability, Virtual Reality and Associated Technologies (ICDVRAT), Gothenburg, 2–4 September 2014, pp. 373–376. The University of Reading, Reading (2014)Google Scholar
  7. 7.
    Holden, M.K.: Virtual environments for motor rehabilitation: review. Cyberpsychol. Behav. 8, 187–211 (2005)CrossRefGoogle Scholar
  8. 8.
    Cho, K.H., Lee, K.J., Song, C.H.: Virtual-reality balance training with a video-game system improves dynamic balance in chronic stroke patients. Tohoku J. Exp. Med. 228, 69–74 (2012)CrossRefGoogle Scholar
  9. 9.
    Bonnet, V., Joukov, V., Kulić, D., Fraisse, P., Ramdani, N., Venture, G.: Monitoring of hip and knee joint angles using a single inertial measurement unit during lower limb rehabilitation. IEEE Sensors J. 16(6), 1557–1564 (2016). Art. no. 7352303CrossRefGoogle Scholar
  10. 10.
    Sun, T., Wang, C., Liu, Q., Lu, Z., Duan, L., Chen, P., Shen, Y., Li, M., Li, W., Liu, Q., Shi, Q., Wang, Y., Qin, J., Wei, J., Wu, Z.: Development of lower limb motion detection based on LPMS. In: 2016 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2016, pp. 243–248 (2016). Art. no. 7784033Google Scholar
  11. 11.
    Zhang, J., Li, M., Song, R., Zhang, X.: Development of a lower limb rehabilitation robot based on free gait and virtual reality. In: 2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014, pp. 808–813 (2014). Art. no. 7090431Google Scholar
  12. 12.
    Zhang, X., Xu, G., Xie, J., Li, M., Pei, W., Zhang, J.: An EEG-driven lower limb rehabilitation training system for active and passive co-stimulation. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2015, November, pp. 4582–4585 (2015). Art. no. 7319414Google Scholar
  13. 13.
    Fitzgerald, D., Kelly, D., Ward, T., Markham, C., Caulfield, B.: Usability evaluation of e-motion: a virtual rehabilitation system designed to demonstrate, instruct and monitor a therapeutic exercise programme. In: Virtual Rehabilitation, pp. 144–149 (2008)Google Scholar
  14. 14.
    Kalawsky, R.S.: VRUSE–a computerised diagnostic tool: for usability evaluation of virtual/synthetic environment systems. Appl. Ergon. 30, 11–25 (1999)CrossRefGoogle Scholar
  15. 15.
    Gil-Gómez, J.A., Manzano, P.H., Albiol, S.P., Aula, C.V., Gil-Gómez H., Lozano, J.A.Q.: SEQ: suitability evaluation questionnaire for virtual rehabilitation systems. In: Proceedings Application in a Virtual Rehabilitation System for Balance Rehabilitation (2012)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Edwin Pruna
    • 1
    Email author
  • Marco Pilatásig
    • 1
  • Hamilton Angueta
    • 1
  • Christian Hernandez
    • 1
  • Ivón Escobar
    • 1
  • Eddie D. Galarza
    • 1
  • Nancy Jacho
    • 1
  1. 1.Universidad de las Fuerzas Armadas ESPESangolquiEcuador

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