Advertisement

Proposal for Muscle Rehabilitation of Lower Limbs Using an Interactive Virtual System Controlled Through Gestures

  • Edwin Pruna
  • Gabriel Corrales
  • Catherine Gálvez
  • Ivón Escobar
  • Luis Mena
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10851)

Abstract

This work presents the development of an interactive virtual rehabilitation system as an assistant tool to help in the rehabilitation process of lower limbs muscles, specifically focused on children from seven years and older who suffer sicknesses that limit the normal movement of the body. The system is mainly based in algorithms that recognize gestures of the user captured through the Microsoft Kinect 2.0. Furthermore, the experimental results are presented and discussed since the point of view of the usability and the advantages that the proposed system achieves.

Keywords

Virtual interface Kinect 2.0 Gestual control Unity 3D 

Notes

Acknowledgements

We thank the “Universidad de las Fuerzas Armadas ESPE” for financing the investigation project number 2016-PIC-0017.

References

  1. 1.
    Hoang, T.C., Dang, H.T., Nguyen, V.D.: Kinect-based virtual training system for rehabilitation. In: Proceedings of the International Conference on IEEE System Science and Engineering (ICSSE), pp. 53–56 (2017)Google Scholar
  2. 2.
    Abresch, R.T., Carter, G.T., Han, J.J., McDonald, C.M.: Exercise in neuromuscular diseases. Phys. Med. Rehabil. Clin. 23(03), 653–673 (2012)CrossRefGoogle Scholar
  3. 3.
    Liao, W.W., McCombe Waller, S., Whitall, J.: Kinect-based individualized upper extremity rehabilitation is effective and feasible for individuals with stroke using a transition from clinic to home protocol. Cogent Med. 1428038 (2018) (just-accepted)Google Scholar
  4. 4.
    Bai, J., Song, A., Xu, B., Nie, J., Li, H.: A novel human-robot cooperative method for upper extremity rehabilitation. Int. J. Soc. Robot. 9(2), 265–275 (2017)CrossRefGoogle Scholar
  5. 5.
    Simonsen, D., Popovic, M.B., Spaich, E.G., Andersen, O.K.: Design and test of a Microsoft Kinect-based system for delivering adaptive visual feedback to stroke patients during training of upper limb movement. Med. Biol. Eng. Comput. 55(11), 1927–1935 (2017)CrossRefGoogle Scholar
  6. 6.
    Albiol-Pérez, S., Gómez, J.A.G., Olmo, E., Soler, A.M.: A virtual fine rehabilitation system for children with cerebral palsy: assesment of the usability of a low-cost system. In: Rocha, Á., Correia, A.M., Adeli, H., Reis, L.P., Costanzo, S. (eds.) WorldCIST 2017. AISC, vol. 570, pp. 619–627. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-56538-5_63CrossRefGoogle Scholar
  7. 7.
    Bejarano, N.C., Maggioni, S., De Rijcke, L., Cifuentes, C.A., Reinkensmeyer, D.J.: Robot-assisted rehabilitation therapy: recovery mechanisms and their implications for machine design. In: Pons, J., Raya, R., González, J. (eds.) Emerging Therapies in Neurorehabilitation II. Biosystems and Biorobotics, vol. 10, pp. 197–223. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-24901-8_8CrossRefGoogle Scholar
  8. 8.
    Levin, M.F., Weiss, P.L., Keshner, E.A.: Emergence of virtual reality as a tool for upper limb rehabilitation: incorporation of motor control and motor learning principles. Phys. Ther. 95(03), 415–425 (2015)CrossRefGoogle Scholar
  9. 9.
    Valdebenito, V.R., Ruiz, R.D.: Relevant aspects in the rehabilitation of children with neuromuscular diseases. Revista Médica Clínica Las Condes 25(02), 295–305 (2014)CrossRefGoogle Scholar
  10. 10.
    Zhu, M.H., Yang, C.J., Yang, W., Bi, Q.: A kinect-based motion capture method for assessment of lower extremity exoskeleton. In: Yang, C., Virk, G., Yang, H. (eds.) Wearable Sensors and Robots. LNEE, vol. 399, pp. 481–494. Springer, Singapore (2017).  https://doi.org/10.1007/978-981-10-2404-7_37CrossRefGoogle Scholar
  11. 11.
    Tannous, H., Istrate, D., Tho, M.H.B., Dao, T.T.: Serious game and functional rehabilitation for the lower limbs. Eur. Res. Telemed./La Recherche Européenne en Télémédecine 5(02), 65–69 (2016)CrossRefGoogle Scholar
  12. 12.
    Zhao, L., Lu, X., Tao, X., Chen, X.: A Kinect-based virtual rehabilitation system through gesture recognition. In: Proceedings of the International Conference on IEEE Virtual Reality and Visualization (ICVRV), pp. 380–384 (2016)Google Scholar
  13. 13.
    Chang, Y.J., Chen, S.F., Huang, J.D.: A Kinect-based system for physical rehabilitation: a pilot Study for young adults with motor disabilities. Res. Dev. Disabil. 32(06), 2566–2570 (2011)CrossRefGoogle Scholar
  14. 14.
    Adinolfi, F., et al.: SmartCARE—an ICT platform in the domain of stroke pathology to manage rehabilitation treatment and telemonitoring at home. In: Pietro, G., Gallo, L., Howlett, R., Jain, L. (eds.) Intelligent Interactive Multimedia Systems and Services 2016. Smart Innovation, Systems and Technologies, vol. 55, pp. 39–49. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-39345-2_4CrossRefGoogle Scholar
  15. 15.
    Abreu, J., Barroso, João, et al.: Assessment of microsoft kinect in the monitoring and rehabilitation of stroke patients. In: Rocha, Á., Correia, A.M., Adeli, H., Reis, L.P., Costanzo, S. (eds.) WorldCIST 2017. AISC, vol. 570, pp. 167–174. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-56538-5_18CrossRefGoogle Scholar
  16. 16.
    Han, S.H., Kim, H.G., Choi, H.J.: Rehabilitation posture correction using deep neural network. In: Proceedings of the International Conference on IEEE Big Data and Smart Computing (BigComp), pp. 400–402 (2017)Google Scholar
  17. 17.
    Caggianese, G., et al.: A rehabilitation system for post-operative heart surgery. In: De Pietro, G., Gallo, L., Howlett, R.J., Jain, L.C. (eds.) KES-IIMSS 2017. SIST, vol. 76, pp. 554–564. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-59480-4_55CrossRefGoogle Scholar
  18. 18.
    Hoda, M., Hoda, Y., Hafidh, B., El Saddik, A.: Predicting muscle forces measurements from kinematics data using kinect in stroke rehabilitation. Multimed. Tools Appl. 77(2), 1885–1903 (2018)CrossRefGoogle Scholar
  19. 19.
    Beaulieu-Boire, L., et al.: Balance rehabilitation using Xbox Kinect among an elderly population: a pilot study. J. Nov. Physiother. 5(02), 261 (2015)Google Scholar
  20. 20.
    Mousavi Hondori, H., Khademi, M.: A review on technical and clinical impact of microsoft kinect on physical therapy and rehabilitation. J. Med. Eng. 2014 (2014)CrossRefGoogle Scholar
  21. 21.
    Baldominos, A., Saez, Y., del Pozo, C.G.: An approach to physical rehabilitation using state-of-the-art virtual reality and motion tracking technologies. Procedia Comput. Sci. 64, 10–16 (2015)CrossRefGoogle Scholar
  22. 22.
    Ge, Z., Fan, L.: Social development for children with autism using kinect gesture games: a case study in Suzhou Industrial Park Renai School. In: Cai, Y., Goei, S., Trooster, W. (eds.) Simulation and Serious Games for Education. Gaming Media and Social Effects, pp. 113–123. Springer, Singapore (2017).  https://doi.org/10.1007/978-981-10-0861-0_8CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Edwin Pruna
    • 1
  • Gabriel Corrales
    • 1
  • Catherine Gálvez
    • 1
  • Ivón Escobar
    • 1
  • Luis Mena
    • 1
  1. 1.Universidad de las Fuerzas Armadas ESPESangolquíEcuador

Personalised recommendations