Advertisement

Virtual Rehabilitation System for Fine Motor Skills Using a Functional Hand Orthosis

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10851)

Abstract

This article describes a virtual rehabilitation system with work and entertainment environments to treat fine motor injuries through an active orthosis. The system was developed in the Unity 3D graphic engine, which allows the patient greater immersion in the rehabilitation process through proposed activities; to identify the movement performed, the Myo armband is used, a device capable of receiving and sending the signals obtained to a mathematical algorithm which will classify these signals and activate the physical hand orthosis completing the desired movement. The benefits of the system is the optimization of resources, infrastructure and personnel, since the therapy will be assisted by the same virtual environment, in addition it allows selecting the virtual environment and the activity to be carried out according to the disability present in the patient. The results show the correct functioning of the system performed.

Keywords

Virtual reality Rehabilitation Unity 3D Orthosis Disability 

Notes

Acknowledgements

The authors would like to thanks to the Corporación Ecuatoriana para el Desarrollo de la Investigación y Academia–CEDIA for the financing given to research, development, and innovation, through the CEPRA projects, especially the project CEPRA-XI-2017-06; Control Coordinado Multi-operador aplicado a un robot Manipulador Aéreo; also to Universidad de las Fuerzas Armadas ESPE, Universidad Técnica de Ambato, Escuela Superior Politécnica de Chimborazo, and Universidad Nacional de Chimborazo, and Grupo de Investigación en Automatización, Robótica y Sistemas Inteligentes, GIARSI, for the support to develop this paper.

References

  1. 1.
    Sanchez, J.S., et al.: Virtual Rehabilitation System for Carpal Tunnel Syndrome Through Spherical Robots. Accepted 2014Google Scholar
  2. 2.
    Naiker, A.: Repetitive Strain Injuries (RSI) - an ayurvedic approach. J. Ayurveda Integr. Med. Sci. 2(2), 170–173 (2017). ISSN 2456-3110Google Scholar
  3. 3.
    Rosales, R.S., Martin-Hidalgo, Y., Reboso-Morales, L., Atroshi, I.: Reliability and construct validity of the Spanish version of the 6-item CTS symptoms scale for outcomes assessment in carpal tunnel syndrome. BMC Musculoskelet. Disord. 17, 115 (2016)CrossRefGoogle Scholar
  4. 4.
    Uehli, K., et al.: Sleep problems and work injuries: a systematic review and meta-analysis. Sleep Med. Rev. 18(1), 61–73 (2014)CrossRefGoogle Scholar
  5. 5.
    Patti, F., et al.: The impact of outpatient rehabilitation on quality of life in multiple sclerosis. J. Neurol. 249(8), 1027–1033 (2002)CrossRefGoogle Scholar
  6. 6.
    Ueki, S., et al.: Development of a hand-assist robot with multi-degrees-of-freedom for rehabilitation therapy. IEEEASME Trans. Mechatron. 17(1), 136–146 (2012)CrossRefGoogle Scholar
  7. 7.
    Chang, W.H., Kim, Y.-H.: Robot-assisted therapy in stroke rehabilitation. J. Stroke 15(3), 174–181 (2013)CrossRefGoogle Scholar
  8. 8.
    Laver, K., George, S., Thomas, S., Deutsch, J.E., Crotty, M.: Virtual reality for stroke rehabilitation. Stroke 43(2), e20–e21 (2012)CrossRefGoogle Scholar
  9. 9.
    Lohse, K.R., Hilderman, C.G.E., Cheung, K.L., Tatla, S., der Loos, H.F.M.V.: Virtual reality therapy for adults post-stroke: a systematic review and meta-analysis exploring virtual environments and commercial games in therapy. PLoS ONE 9(3), e93318 (2014)CrossRefGoogle Scholar
  10. 10.
    North, M.M., North, S.M., Coble, J.R.: Virtual reality therapy: an effective treatment for the fear of public speaking. Int. J. Virtual Real. IJVR 03(3), 1–6 (2015)Google Scholar
  11. 11.
    Turolla, A., et al.: Virtual reality for the rehabilitation of the upper limb motor function after stroke: a prospective controlled trial. J. Neuroeng. Rehabil. 10, 85 (2013)CrossRefGoogle Scholar
  12. 12.
    Romero, P., León, A., Arteaga, O., Andaluz, V.H., Cruz, M.: Composite materials for the construction of functional orthoses. Accepted 2017Google Scholar
  13. 13.
    Benalcázar, M.E., Jaramillo, A.G., Jonathan, A., Zea, A., Páez, V.H.: Andaluz: hand gesture recognition using machine learning and the Myo armband. In: 2017 25th European Signal Processing Conference (EUSIPCO), pp. 1040–1044 (2017)Google Scholar
  14. 14.
    Maroukis, B.L., Chung, K.C., MacEachern, M., Mahmoudi, E.: Hand trauma care in the united states: a literature review. Plast. Reconstr. Surg. 137(1), 100e–111e (2016)CrossRefGoogle Scholar
  15. 15.
    Feron, L.O., Boniatti, C.M., Arruda, F.Z., Butze, J., Conde, A.: lesões por esforço repetitivo em cirurgiões-dentistas: uma revisão da literatura. Rev. Ciênc. Saúde 16(2), 79–86 (2014)Google Scholar
  16. 16.
    Putz-Anderson, V.: Cumulative Trauma Disorders. CRC Press, Boca Raton (2017)Google Scholar
  17. 17.
    Oktayoglu, P., Nas, K., Kilinç, F., Tasdemir, N., Bozkurt, M., Yildiz, I.: Assessment of the presence of carpal tunnel syndrome in patients with diabetes mellitus, hypothyroidism and acromegaly. J. Clin. Diagn. Res. JCDR 9(6), OC14–OC18 (2015)Google Scholar
  18. 18.
    Villafañe, J., Cleland, J., Fernánde-de-las-Peñas, C.: the effectiveness of a manual therapy and exercise protocol in patients with thumb carpometacarpal osteoarthritis: a randomized controlled trial. J. Orthop. Sports Phys. Ther. 43(4), 204–213 (2013)CrossRefGoogle Scholar
  19. 19.
    Langer, D., Maeir, A., Michailevich, M., Applebaum, Y., Luria, S.: Using the international classification of functioning to examine the impact of trigger finger. Disabil. Rehabil. 38(26), 2530–2537 (2016)CrossRefGoogle Scholar
  20. 20.
    da Silva Dulci Medeiros, M., Santana, D.V.G., de Souza, G.D., Souza, L.R.Q.: Tenossinovite de Quervain: aspectos diagnósticos. Rev. Med. E Saúde Brasília 5(2), 307–312 (2016)Google Scholar
  21. 21.
    Werthel, J.-D., Cortez, M., Elhassan, B.T.: Modified percutaneous trigger finger release. Hand Surg. Rehabil. 35(3), 179–182 (2016)CrossRefGoogle Scholar
  22. 22.
    Chang, K.-H.: Motion Simulation and Mechanism Design with SOLIDWORKS Motion 2016. SDC Publications (2016)Google Scholar
  23. 23.
    Andaluz, V.H., Pazmiño, A.M., Pérez, J.A., Carvajal, C.P., Lozada, F., Lascano, J., Carvajal, J.: Training of tannery processes through virtual reality. In: De Paolis, L.T., Bourdot, P., Mongelli, A. (eds.) AVR 2017. LNCS, vol. 10324, pp. 75–93. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-60922-5_6CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Universidad de Las Fuerzas Armadas ESPESangolquíEcuador
  2. 2.Escuela Politécnica Nacional EPNQuitoEcuador

Personalised recommendations