Use of Brain-Machine Interface technology in the rehabilitation of patients

Authors

DOI:

https://doi.org/10.33448/rsd-v9i11.10016

Keywords:

Rehabilitation; Mobility Limitation; Technology.

Abstract

In the last few decades, there have been advances in the field of innovative technologies used for the rehabilitation of people with a motor disability. A great example is the Brain-Machine Interface (BMI) technologies, which allow the control of machines through the brain activity of individuals and contributes to a reorganization of their motor and sensory systems. Thus, several evidences have suggested the use of technologies in the rehabilitation of these patients. The aim of this study was to perform a literature review on the use of technologies applied to motor rehabilitation. To carry out this study, a search for scientific articles was performed in the Pubmed, Scielo and Lilacs databases, in addition to the dissertations and theses found on the CAPES database. There were a total of 24 references, published between 2002 and 2020. According to the literature studied, there is an increase in resources that use technologies as therapeutic options. Many of the conventional interventions are being replaced or associated with these innovative technologies. With the advent of BMI technology and its use in human beings, a technological revolution can be observed in several biomedical areas, thus allowing a multidisciplinary application in the rehabilitation of motor, sensory or cognitive functions in patients. Despite the advances, this subject still shows controversies and before a broad recommendation, more randomized studies and a greater ethical recommendation on the subject will be needed.

References

Alcantara, J. G. D. (2020). Tecnologias assistivas para a mobilidade de pessoas com deficiência. (Doctoral dissertation). http://repositorio.uninove.br/xmlui/handle/12 3456789/1340

Birbaumer, N., & Cohen, L. G. (2007). Brain–computer interfaces: communication and restoration of movement in paralysis. The Journal of Physiology, 579(3), 621-636. http://doi.wiley.com/10.1113/jphysiol.2006.125633.

Brandão, A. F., Brasil, G. J. C., Dias, D. R. C., Almeida, S. R. M., Castelhano, G., & Trevelin, L. C. (2014). Realidade Virtual e reconhecimento de gestos aplicada as áreas de saúde. Tendências e Técnicas em Realidade Virtual e Aumentada, 1(4), 33-48. https://d1wqtxts1xzle7.cloudfront.net/59612803/MC_SVR_201420190608-12881-1l8pqmu. pdf?1560021857=&response-content-disposition=inline%3B+filename%3DTENDENC IAS_E_TECNICAS_EM_REALIDADE_VIRTU.pdf&Expires=1603146177&Signature=Q~1t9SW-VNwOC4Wxfvi74becZhWgct9ViJvjS1ZkHKk12QWmSbZzjM1mdnnOEZo45Eg RVVeQWP~8jbEu4qBv6z49mhvJ0765WqbJt0Z55-Vgf95Ui9TKiUGE6kIaULlpIaDvpCgc J0cufdpjfUpMriQGhM-yVw93YgVzVgmAoaQQgpddycj~Xiinx-sJlhG6A1Xw5NRd 0o7vr54Bi2JSxVXyhfeu2wDy-0Wxy6F3nbNSj-j8S-1FIF5rkqfhKacSmxuvVj25xgMJC Q9jbJjKV6wm9QNP~dJeGpLqXU3apB1Akpzn8bgevR4E~wQEywaibpcle6aqzW2 R22LsYpAFSg__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA#page=33

Burwell, S., Sample, M., & Racine, E. (2017). Ethical aspects of brain computer interfaces: a scoping review. BMC Medical Ethics, 18(1), 1-11. https://bmcmedeth ics.biomedcentral.com/articles/10.1186/s12910-017-0220-y

Caiana, T. L., de Lima Nogueira, D., & Dantas de Lima, A. C. (2016). A realidade virtual e seu uso como recurso terapêutico ocupacional: revisão integrativa. Cadernos de Terapia Ocupacional da UFSCar, 24(3), 575-589.http://www.cadernosdeto.ufscar.br/inde x.php/cadernos/article/view/1218/752

Caria, A., Weber, C., Brötz, D., Ramos, A., Ticini, L. F., Gharabaghi, A., & Birbaumer, N. (2011). Chronic stroke recovery after combined BCI training and physiotherapy: a case report. Psychophysiology, 48(4), 578-582. http://doi.wiley.com/10.1111/j.1469-8986.2010.01117.x.

Coscia, M., Wessel, M. J., Chaudary, U., Millán, J. D. R., Micera, S., Guggisberg, A., & Hummel, F. C. (2019). Neurotechnology-aided interventions for upper limb motor rehabilitation in severe chronic stroke. Brain, 142(8), 2182-2197. https://academic.oup.com/brain/article/142/8/2182/5524504

Daly, J. J., & Wolpaw, J. R. (2008). Brain–computer interfaces in neurological rehabilitation. The Lancet Neurology, 7(11), 1032-1043. https://linkinghub.elsevier.com/retrieve /pii/S1474442208702230.

Djebrouni, M., & Wolbring, G. (2020). Impact of robotics and human enhancement on occupation: what does it mean for rehabilitation?. Disability and Rehabilitation, 42(11), 1518-1528. https://www.tandfonline.com/doi/full/10.1080/09638288.2018.1527401.

Giansanti, D., Maccioni, G., & Morelli, S. (2008). An experience of health technology assessment in new models of care for subjects with Parkinson’s disease by means of a new wearable device. Telemed e-Health, 14(5), 467-472. https://www.liebertpub.com/doi/10.1089/tmj.2007.0078.

Miśkiewicz, J. (2019). The merger of natural intelligence with artificial intelligence, with a focus on Neuralink company. Virtual Economics, 2(3), 22-29. https://virtual-economics.eu/index.php/VE/article/view/28

Nabavi, S., Fox, R., Proulx, C. D., Lin, J. Y., Tsien, R. Y., & Malinow, R. (2014). Engineering a memory with LTD and LTP. Nature, 511(7509), 348-352. http://www.nature.com/articles/nature13294.

Patel, S., Park, H., Bonato, P., Chan, L., & Rodgers, M. (2012). A review of wearable sensors and systems with application in rehabilitation. Journal of Neuroengineering and Rehabilitation, 9(1), 1-17. 2012;9(21):1-17. https://jneuroengrehab.biomed central.com/articles/10.1186/1743-0003-9-21.

Rosenfeld, J. V., & Wong, Y. T. (2017). Neurobionics and the brain–computer interface: current applications and future horizons. Medical Journal of Australia, 206(8), 363-368. https://www.mja.com.au/system/files/issues/206_08/10.5694mja16.01011.pdf

Ruffino, C., Papaxanthis, C., & Lebon, F. (2017). Neural plasticity during motor learning with motor imagery practice: Review and perspectives. Neuroscience, 341(1), 61-78.https://doi.org/10.1016/j.neuroscience.2016.11.023

Sazonov, E. S., Fulk, G., Sazonova, N., & Schuckers, S. (2009). Automatic recognition of postures and activities in stroke patients. In 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 2200-2203). IEEE.

http://ieeexplore.ieee.org/document/5334908/.

Steeves, J. K., & Harris, L. R. (2013). Plasticity in Sensory Systems. Cambridge University Press. https://books.google.com.br/books?hl=pt-BR&lr=&id=ckCozisvTlsC&oi=fnd&p g=PA1&d=Steeves+JKE,+Harris+LR.+Plasticity+in+Sensory+Systems.+1st+ed.+Cambridge:+Cambridge+University+Press%3B+2012.&ots=AQZiiKW6s_&sig=NX1zciFVGAkJWH0GXHN-I0s708Y#v=onepage&q&f=false

Schlaggar, B. L., & Power, J. D. (2017). Neural plasticity across the lifespan. https://allenamente.net/wp-content/uploads/2017/10/VUOI-SAPERNE-DI-PIU.pdf

Tonegawa, S., Pignatelli, M., Roy, D. S., & Ryan, T. J. (2015). Memory engram storage and retrieval. Current Opinion in Neurobiology, 35, 101-109. https://doi.org/10.1016/j.conb.2015.07.009

Ushiba, J. (2019). Brain-Machine Interface and Neuro-Rehabilitation. Brain and nerve= Shinkei kenkyu no shinpo, 71(7), 793-804. https://europepmc.org/article/med/31289253

Wada, K., Ono, Y., Kurata, M., Ito, M. I., Minakuchi, M. T., Kono, M., & Tominaga, T. (2019). Development of a Brain-machine Interface for Stroke Rehabilitation Using Event-related Desynchronization and Proprioceptive Feedback. Advanced Biomedical Engineering, 8(1), 53-59. https://www.jstage.jst.go.jp/article/abe/8/0/8_8_53/_article/-char/ja/

Wenderoth, N. (2018). Motor learning triggers neuroplastic processes while awake and during sleep. Exercise and Sport Sciences Reviews, 46(3), 152-159. http://journals.lww.com/00003677-201807000-00004.

Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., & Vaughan, T. M. (2002). Brain–computer interfaces for communication and control. Clinical Neurophysiology, 113(6), 767-791. https://doi.org/10.1016/S1388-2457(02)00057-3

Xu, T., Yu, X., Perlik, A. J., Tobin, W. F., Zweig, J. A., Tennant, K., & Zuo, Y. (2009). Rapid formation and selective stabilization of synapses for enduring motor memories. Nature, 462(7275), 915-919. http://www.nature.com/articles/nature08389.

Published

05/12/2020

How to Cite

NOLÊTO, B. C. .; CAMPELO, F. R. de A. P. .; RODRIGUES, K. C. S. .; RIBEIRO, L. M.; SALVIANO, M. . Use of Brain-Machine Interface technology in the rehabilitation of patients. Research, Society and Development, [S. l.], v. 9, n. 11, p. e84691110016, 2020. DOI: 10.33448/rsd-v9i11.10016. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/10016. Acesso em: 26 dec. 2024.

Issue

Section

Health Sciences