Virtual Reality Training of Myoelectric Prosthesis with the Use of Sensory Feedback and Serious Game Techniques
Resumo
In this thesis, we propose a system that uses immersive Virtual Reality (iVR) and EMG signal processing (muscle activity) to provide a training environment for amputees who are supposed to use a myoelectric prosthesis. We also investigate the efficiency of learning how to control a virtual prosthesis with and without sensory feedback. Our results show that virtual training can be greatly improved when proper tactile feedback is provided, especially for myoelectric controlled prostheses.
Palavras-chave:
Sensory feedback, Immersive Virtual Reality, myoelectric prosthesis, prosthetic training
Referências
J. M. Churko, A. Mehr, A. G. Linassi, and A. Dinh, “Sensor evaluation for tracking upper extremity prosthesis movements in a virtual environment,” in Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009, 2009, vol. 2009, pp. 2392–2395.
M. Melero et al., “Upbeat: Augmented Reality-Guided Dancing for Prosthetic Rehabilitation of Upper Limb Amputees,” J. Healthc. Eng., vol. 2019, 2019.
K. Li, P. Boyd, Y. Zhou, Z. Ju, and H. Liu, “Electrotactile Feedback in a Virtual Hand Rehabilitation Platform: Evaluation and Implementation,” IEEE Trans. Autom. Sci. Eng., vol. 16, no. 4, pp. 1556–1565, Oct. 2019.
D. Blana, T. Kyriacou, J. M. Lambrecht, and E. K. Chadwick, “Feasibility of using combined EMG and kinematic signals for prosthesis control: A simulation study using a virtual reality environment,” J. Electromyogr. Kinesiol., vol. 29, pp. 21–27, Aug. 2016.
K. Odette and Q. Fu, “A Physics-based Virtual Reality Environment to Quantify Functional Performance of Upper-limb Prostheses,” in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2019, vol. 2019, pp. 3807–3810.
T. Shibanoki, G. Nakamura, T. Tsuji, K. Hashimoto, and T. Chin, “A New Approach for Training on EMG-based Prosthetic Hand Control,” in LifeTech 2020 - 2020 IEEE 2nd Global Conference on Life Sciences and Technologies, 2020, pp. 307–308.
M. Melero et al., “Upbeat: Augmented Reality-Guided Dancing for Prosthetic Rehabilitation of Upper Limb Amputees,” J. Healthc. Eng., vol. 2019, 2019.
K. Li, P. Boyd, Y. Zhou, Z. Ju, and H. Liu, “Electrotactile Feedback in a Virtual Hand Rehabilitation Platform: Evaluation and Implementation,” IEEE Trans. Autom. Sci. Eng., vol. 16, no. 4, pp. 1556–1565, Oct. 2019.
D. Blana, T. Kyriacou, J. M. Lambrecht, and E. K. Chadwick, “Feasibility of using combined EMG and kinematic signals for prosthesis control: A simulation study using a virtual reality environment,” J. Electromyogr. Kinesiol., vol. 29, pp. 21–27, Aug. 2016.
K. Odette and Q. Fu, “A Physics-based Virtual Reality Environment to Quantify Functional Performance of Upper-limb Prostheses,” in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2019, vol. 2019, pp. 3807–3810.
T. Shibanoki, G. Nakamura, T. Tsuji, K. Hashimoto, and T. Chin, “A New Approach for Training on EMG-based Prosthetic Hand Control,” in LifeTech 2020 - 2020 IEEE 2nd Global Conference on Life Sciences and Technologies, 2020, pp. 307–308.
Publicado
18/10/2021
Como Citar
CAVALCANTE, Reidner; SOARES, Alcimar; LAMOUNIER, Edgard.
Virtual Reality Training of Myoelectric Prosthesis with the Use of Sensory Feedback and Serious Game Techniques. In: WORKSHOP DE TESES E DISSERTAÇÕES - SIMPÓSIO DE REALIDADE VIRTUAL E AUMENTADA (SVR), 23. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 9-10.
DOI: https://doi.org/10.5753/svr_estendido.2021.17650.
