Abstract
Using Serious Games (SG) in virtual rehabilitation is favorable since it allows users to evolve in their training process, while enjoying the tasks and challenges proposed. In this paper, the authors present a pilot test that uses an immersive Virtual Reality (iVR)-based Serious Game to simulate a myoelectric prosthesis, which is controlled by EMG signal processing (muscle activity reading). EMG signals, as in real life, control the opening and closing of the virtual prosthesis, and vibrational elements placed on the user’s forearm provide sensory feedback to enhance the feeling of touching. Evidence presented in this work shows that users utilizing tactile feedback demonstrated improved performance and the Serious Game helped to accomplish the training tasks.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Global Lower Extremity Amputation Study Group Unwin N.: Epidemiology of lower extremity amputation in centers in Europe, North America and East Asia. J. Br. Surg. 87(3), 328–37 (2000)
Mattioli, F.E.R., Lamounier, E.A., Cardoso, A., Soares, A.B., Andrade, A.O.: Classification of EMG signals using artificial neural networks for virtual hand prosthesis control. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 7254–7257 (2011)
Putrino, D., Wong, Y.T., Weiss, A., Pesaran, B.: A training platform for many-dimensional prosthetic devices using a virtual reality environment. J. Neurosci. Meth. 244, 68–77 (2015)
Li, K., Boyd, P., Zhou, Y., Ju, Z., Liu, H.: Electrotactile feedback in a virtual hand rehabilitation platform: evaluation and implementation. IEEE Trans. Autom. Sci. Eng. 16(4), 1556–1565 (2019)
Sharma, A., et al.: A mixed-reality training environment for upper limb prosthesis control. In: 2018 IEEE Biomedical Circuits and Systems Conference Proceedings, pp. 1–4, IEEE. Cleveland, Ohio, USA (2018)
De Gloria, A., Bellotti, F., Berta, R.: Serious games for education and training. Int. J. Ser. Games 1(1), (2014)
Sekhavat, Y.A., Nomani, P.: A comparison of active and passive virtual reality exposure scenarios to elicit social anxiety. Int. J. Serious Games, 4(2), 3–15 (2017)
Garcia-Agundez, A., et al.: PDPuzzleTable: a leap motion exergame for dual-tasking rehabilitation in parkinson’s disease. design and study protocol. In: van der Spek, E., Göbel, S., Do, E.-L., Clua, E., Baalsrud Hauge, J. (eds.) ICEC-JCSG 2019. LNCS, vol. 11863, pp. 402–406. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-34644-7_35
Mitgutsch, N., Alvarado, K.: Purposeful by design: a serious game design assessment framework. In: International Conference on the Foundations of Digital Games Proceedings, pp. 121– 128. ACM (2012)
Kuttuva, M., Burdea, G., Flint, J., Craelius, W.: Manipulation practice for upper-limb amputees using virtual reality. Presence: Teleoper. Virt. Environ. 14(2), 175–182 (2005)
Melero, M., et al.: Upbeat: augmented reality-guided dancing for prosthetic rehabilitation of upper limb amputees. J. Healthcare Eng. (2019)
Churko, J.M., Mehr, A., Linassi, A.G., Dinh, A.: Sensor evaluation for tracking upper extremity prosthesis movements in a virtual environment. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society Proceedings. IEEE (2009)
Atzori, M., et al.: Electromyography data for non-invasive naturally-controlled robotic hand prostheses. Sci. data 1(1), 1–13 (2014)
Blana, D., Kyriacou, T., Lambrecht, J.M., Chadwick, E.K.: Feasibility of using combined EMG and kinematic signals for prosthesis control: a simulation study using a virtual reality environment. J. Electromyogr. Kinesiol. 29, 21–27 (2016)
Odette, K., Fu, Q.: A physics-based virtual reality environment to quantify functional performance of upper-limb prostheses. In: 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society Proceedings, pp. 3807–3810 (2019)
Phelan, I., Arden, M., Garcia, C., Roast, C.: Exploring virtual reality and prosthetic training. In: IEEE Virtual Reality, pp. 353–354. IEEE (2015)
Shibanoki, T., Nakamura, G., Tsuji, T., Hashimoto, K., Chin, T.: A new approach for training on EMG-based prosthetic hand control. In: 2nd Global Conference on Life Sciences and Technologies Proceedings, pp. 307–308. IEEE (2020)
Earley, E.J., Kaveny, K.J., Johnson, R.E., Hargrove, L.J., Sensinger, J.W.: Joint-based velocity feedback to virtual limb dynamic perturbations. In: 2017 International Conference on Rehabilitation Robotics, pp. 1313–1318. IEEE (2017)
Johansen, D., et al.: A comparative study of virtual hand prosthesis control using an inductive tongue control system. Assist. Technol. 28(1), 22–29 (2016)
Lamounier, E., Lopes, K., Cardoso, A., Andrade, A., Soares, A.: On the use of Virtual and augmented reality for upper limb prostheses training and simulation. In: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC’10, pp. 2451–2454 (2010)
Johnson-Glenberg, M.C.: Immersive VR and education: embodied design principles that include gesture and hand controls. Front. Robot. AI 5, 81 (2018)
Burke, J.W., McNeill, M.D.J., Charles, D.K., Morrow, P.J., Crosbie, J.H., McDonough, S.M.: Optimising engagement for stroke rehabilitation using serious games. Vis. Comput. 25(12), 1085–1099 (2009)
Figueiredo, S.: Nine Hole Peg Test (NHPT). Stroke Engine
Kyberd, P., Hussaini, A., Maillet, G.: Characterisation of the clothespin relocation test as a functional assessment tool. J. Rehab. Assistive Technol. Eng. 5, 2055668317750810 (2018)
Alves, T., Gama, S., Melo, F.S.: Flow adaptation in serious games for health. In: 6th International Conference on Serious Games and Applications for Health Proceedings. IEEE (2018)
Cavalcante, R., Lamounier, E., Cardoso, A., Soares, A., de Lima, G.M.: Development of a serious game for rehabilitation of upper limb amputees. In 2018 20th Symposium on Virtual and Augmented Reality (SVR), pp. 99–105. IEEE, October 2018
Luo, T., Cai, N., Li, Z., Pan, Z., Yuan, Q.: VR-DLR: a serious game of somatosensory driving applied to limb rehabilitation training. In: Nunes, N.J., Ma, L., Wang, M., Correia, N., Pan, Z. (eds.) ICEC 2020. LNCS, vol. 12523, pp. 51–64. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-65736-9_4
Acknowledgments
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001, Autodesk Foundation and Qatar University under the grant IRCC-2019–001.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 IFIP International Federation for Information Processing
About this paper
Cite this paper
Cavalcante, R., Gaballa, A., Cabibihan, JJ., Soares, A., Lamounier, E. (2021). A VR-Based Serious Game Associated to EMG Signal Processing and Sensory Feedback for Upper Limb Prosthesis Training. In: Baalsrud Hauge, J., C. S. Cardoso, J., Roque, L., Gonzalez-Calero, P.A. (eds) Entertainment Computing – ICEC 2021. ICEC 2021. Lecture Notes in Computer Science(), vol 13056. Springer, Cham. https://doi.org/10.1007/978-3-030-89394-1_36
Download citation
DOI: https://doi.org/10.1007/978-3-030-89394-1_36
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-89393-4
Online ISBN: 978-3-030-89394-1
eBook Packages: Computer ScienceComputer Science (R0)