Brain computer-interface

new perspectives for rehabilitation

Authors

  • Sergio Machado Educador Físico, Doutorando em Saúde Mental, Laboratório de Mapeamento Cerebral e Integração Sensório-Motora (IPUB/UFRJ), Instituto Brasileiro de Biociências Neurais (IBBN), Bolsista Capes, Rio de Janeiro-RJ, Brasil.
  • Marlo Cunha Educador Físico, Doutorando em Saúde Mental, Laboratório de Mapeamento Cerebral e Integração Sensório-Motora (IPUB/UFRJ), Instituto Brasileiro de Biociências Neurais (IBBN), Bolsista CNPq, Rio de Janeiro-RJ, Brasil.
  • Bruna Velasques Psicóloga, Mestranda em Saúde Mental, Laboratório de Mapeamento Cerebral e Integração Sensório-Motora (IPUB/UFRJ), Instituto Brasileiro de Biociências Neurais (IBBN), Bolsista Capes, Rio de Janeiro-RJ, Brasil.
  • Daniel Minc Educador Físico, Mestrando em Saúde Mental, Laboratório de Mapeamento Cerebral e Integração Sensório-Motora (IPUB/UFRJ), Instituto Brasileiro de Biociências Neurais (IBBN), Rio de Janeiro-RJ, Brasil.
  • Victor Hugo Bastos Fisioterapeuta, Doutor em Saúde Mental, Laboratório de Mapeamento Cerebral e Integração Sensório-Motora (IPUB/UFRJ), Instituto Brasileiro de Biociências Neurais (IBBN), Rio de Janeiro-RJ, Brasil
  • Henning Budde Educador Físico, Professor Doutor do Departamento de Ciência de Movimento e Treinamento do Instituto de Ciências do Esporte, Humboldt University Berlin, Alemanha.
  • Maurício Cagy Engenheiro Biomédico, Professor Adjunto Doutor da Divisão de Epidemiologia e Bioestatística, Instituto de Saúde Comunitária, Universidade Federal Fluminense (UFF), Rio de Janeiro, Brasil.
  • Roberto Piedade Médico, Professor Adjunto Doutor do Laboratório de Mapeamento Cerebral e Integração Sensório-Motora (IPUB/UFRJ).
  • Pedro Ribeiro Educador Físico, Professor Adjunto Doutor do Departamento de Biociências da Atividade Física, Escola de Educação Física e Desportos (EEFD/UFRJ); Professor do Laboratório de Mapeamento Cerebral e Integração Sensório-Motora (IPUB/UFRJ), Instituto Brasileiro de Biociências Neurais (IBBN), Rio de Janeiro-RJ, Brasil.

DOI:

https://doi.org/10.34024/rnc.2009.v17.8525

Keywords:

User computer interface, Rehabilitation, Review

Abstract

Brain computer interface (BCI) is a technique that utilizes electric signals which can be detected from scalp, cortical surface or brain subcortical areas to activate external devices such as computers, interruptors or prosthesis, allowing that users can communicate with the outside world. The aim of this study was related to basic concepts and principles of BCI technique and highlights the more recent experimental advances that may become viable clinical applications in the next years related to rehabilitation of the severely limited patients. The studies demonstrated that there are two important applications of a BCI system at present, the promoting of a new channel of communication and the restoration of motor functions through the use of neuroprothesis. These studies point to the invasive method as the most appropriate to control neuroprothesis. It was observed that the motor functions restoration setting in relation to severely limited patients tend to grow quite a lot in the next years. Fact attributed to great demand of questions that still remains without reply and that come being incessantly investigated

Metrics

Metrics Loading ...

Downloads

Download data is not yet available.

References

Birbaumer N, Cohen LG. Brain-computer interfaces: communication and restoration of movement in paralysis. J Physiol 2007;579:621-36.

Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM. Brain-computer interfaces for communication and control. Clin Neurophysiol 2002;113:767-91.

Serruya MD, Hatsopoulos NG, Paninski L, Fellows MR, Donoghue JP. Instant neural control of a movement signal. Nature 2002; 416:141-42.

Taylor DM, Tillery DM, Tillery SI, Schwartz AB. Direct cortical control of 3D neuroprosthetic devices. Science 2002;296:1829-32.

Lebedev MA, Carmena JM, O’doherty JE, Zacksenhouse M, Henríquez CS, Príncipe JC, et al. Cortical ensemble adaptation to represent velocity of an artificial actuator controlled by a brain–machine interface. J Neurosci 2005; 2:4681-93.

Bayliss JD, Ballard DH. A virtual reality testbed for brain–computer interface research. IEEE Trans Rehabil Eng 2000;8:188-90.

Biran R, Noble MD, Tresco PA. Directed nerve outgrowth is enhanced by engineered glial substrates. Exp Neurol 2003;184:141-52.

Birbaumer N. Brain–computer-interface research: coming of age. Clin Neurophysiology 2006;117:479-83.

Birbaumer N, Kubler A, Perelmouter J, Taub E, Flor H. A spelling device for the paralyzed. Nature 1999;398:297-8.

Birbaumer N, Kubler A, Ghanayim N, Hinterberger T, Perelmouter J, Kociser J, et al. The thought translation device (TTD) for completely paralyzed patients. IEEE Trans Rehabil Eng 2000;8:190-3.

Bossetti CA, Carmena JM, Nicolelis MA, Wolf PD. Transmission latencies in a telemetry linked brain–machine interface. IEEE Trans Biomed Eng 2004;51:919-24.12.Breuer T, Fishlock N. First observation of tool use in wild gorillas. PLOS Biol 2005;3:e380.

Brockwell AE, Rojas AL, Kass RE. Recursive Bayesian decoding of motor cortical signals by particle filtering. J Neurophysiol 2004;91:1899-907.

Brown EN, Kass RE, Mitra PP. Multiple neural spike train data analysis: state-of-the-art and future challenges. Nat Neurosci 2004;7:456-61.

Carmena JM, Lebedev MA, Crist RE, O’doherty JE, Santucci DM, Dimitrov DF, et al. Learning to control a brain-machine interface for reaching and grasping by primates. PLOS Biol 2003;1:e42.

Carmena JM, Lebedev MA, Henriquez CS, Nicolelis MA. Stable ensemble performance with single neuron variability during reaching movements in primates. J Neurosci 2005;25:10712-6.

Chapin JK. Neural prosthetic devices for quadriplegia. Curr Opin Neurobiol 2000;13:671-5.

Nicolelis MAL, Birbaumer N, Mueller KL. Special issue on brain machine interfaces. IEEE Trans Biomed Eng 2004;51:877-1087.

Chapin JK, Moxon KA, Markowitz RS, Nicolelis MA. Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex. Nat Neurosci 1999;2:664-70.

Piccione F, Giorgi F, Tonin P, Priftis K, Giove S, Silvoni S, et al. P300-based brain computer interface: Reliability and performance in healthy and paralysed participants. Clin Neurophysiol 2006;117:531–7.

Sellers EW, Donchin E. A P300-based brain–computer interface: Initial tests by ALS patients. Clin Neurophysiol 2006;117:538–48.

Hinterberger T, Veit R, Wilhelm B, Weiskopf N, Vatine JJ, Birbaumer N. Neuronal mechanisms underlying control of a brain–computer interface. Eur J Neurosci 2005;21:3169-81.

Kubler A, Kotchoubey B, Kaisco J, Wolpaw Jr, Birbaumer N. Brain–computer communication: unlocking the locked in. Psychol Bull 2001;127:358–75.

Kubler A, Neumann N, Kaiser J, Kotchoubey B, Hinterberg T, Birbaumer N. Brain–computer communication: self regulation of slow cortical potentials for verbal communication. Arch Phys Med Rehabil 2001;82:1533-9.

Obermaier B, Neuper C, Guger C, Pfurtscheller G. Information transfer rate in a five-classes brain–computer interface. IEEE Trans Neural Sys Rehabil Eng 2001;9:283-8.

Obermaier B, Muller GR, Pfurtscheller G. Virtual keyboard controlled by spontaneous EEG activity. IEEE Trans Neural Syst Rehabil Eng 2003;11:422-6.

Sheikh H, Mcfarland DJ, Sarnacki WA, Wolpaw JR. Electroencephalographic (EEG)-based communication: EEG control versus system performance in humans. Neurosci Let 2003;345:89-92.

Wolpaw JR. Brain-computer interfaces (ICCs) for communication and control: a mini-review. Suppl Clin Neurophysiol 2004;57:607-13.

Middendorf M, Mcmillan G, Calhoun G, Jones KS. Brain–computer interfaces based on the steady-state visual-evoked response. IEEE Trans Rehabil Eng 2000;8:211-4.

Scherberger H, Jarvis MR, Andersen RA. Cortical local field potential encodes movement intentions in the posterior parietal cortex. Neuron 2005;46:347-54.

Schwartz Ab, Taylor Dm, Tillery SI. Extraction algorithms for cortical for cortical control of arm prosthetics. Curr Opin Neurobiol 2001;11:701-7.

Guger C, Edlinger G, Harkam W, Niedermayer I, Pfurtscheller G. How many people are able to operate an EEG-based brain-computer interface (ICC). IEEE Trans Neural Syst Rehabil Eng 2003;11:145-7.

Kostov A, Polak M. Parallel man-machine training in development of EEG-based cursor control. IEEE Trans Rehabil Eng 2000;8:203-5.

Lauer RT, Peckham PH, Kilgore KL. EEG-based control of a hand grasps neuroprosthesis. Neuroreport 1999;10: 1767-71.

Hochberg LR, Serruya MD, Friehs GM, Mukand JA, Saleh M, Caplan AH, et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 2006;442:164-71.

Wessber GJ, Stamhaugh CR, Kralik JD, Beck PD, Laubach M, Chapin K, et al. Real-time prediction of hand trajectory by ensembles of cortical neurons in primates. Nature 2000;408:361-5.

Serruya M, Hatsopoulos N, Fellows M, Paninski L, Donoghue J. Robustness of neuroprosthetic decoding algorithms. Biol Cybern 2003;88:219-28.

Patil PG, Carmena JM, Nicolelis MA, Turner DA. Ensemble recordings of human subcortical neurons as a source of motor control signals for a brain–machine interface. Neurosurgery 2004;55:1-10.

Kennedy Pr, Bakay Ra, Moore Mm, Adams K, Goldwaithe J. Direct control of a computer from the human central nervous system. IEEE Trans Rehabil Eng 2000;8:198-202.

Shenoy KV, Meeker D, Cao S, Kureshi SA, Pesaran B, Buneo CA, et al. Neural prosthetic control signals from plan activity. Neuroreport 2003;14:591-6.

Graimann B, Huggins JE, Schlogl A, Levine SP, Pfurtscheller G. Detection of movement-related desynchronization patterns in ongoing single-channel electrocorticogram. IEEE Trans Neural Syst Rehabil Eng 2003;11:276-81.

Muller GR, Neuper C, Rupp R, Keinrath C, Gerner HJ, Pfurtscheller G. Event-related beta EEG changes during wrist movements induced by functional electrical stimulation of forearm muscles in man. Neurosci Lett 2003; 340:143-7.

Neuper C, Muller GR, Kubler A, Birbaumer N, Pfurtscheller G. Clinical application of an EEG-based brain-computer interface: a case study in a patient with severe motor impairment. Clin Neurophysiol 2003;114:399-409.

Pfurtscheller G, Müller GR, Pfurtscheller J, Gerner HJ, Rupp R. ‘Thought’-control of functional electrical stimulation to restore hand grasp in a patient with tetraplegia. Neurosci Lett 2003;351:33-6.

Hatsopoulos N, Joshi J, O’Leary JG. Decoding continuous and discrete motor behaviors using motor and premotor cortical ensembles. J Neurophysiol 2004;92:1165-74.

Mcfarland DJ, Wolpaw JR. EEG-based communication and control: speed-accuracy relationships. Appl Psychophysiol Biofeedback 2003;28:217-31.

Helms Tillery SI, Taylor DM, Schwartz AB. Training in cortical control of neuroprosthetic devices improves signal extraction from small neuronal ensembles. Rev Neuroscienc 2003;14:107-19.

Wolpaw J, Mcfarland D. Control of a two-dimensional movement signal by a non-invasive brain–computer interface in humans. Proc Natl Acad Sci 2005;101:17849-54.

Isaacs RE, Weber DJ, Schwartz AB. Work toward real-time control of a cortical neural prothesis. IEEE Trans Rehabil Eng 2000;8:196-8.

Kennedy PR, Bakay RA. Restoration of neural output from a paralyzed patient by a direct brain connection. NeuroReport 1998;9:1707-11.

Fetz EE. Real-time control of a robotic arm by neuronal ensembles. Nat Neurosci 1999;2:583-4.

Taylor DM, Tillery SI, Schwartz AB. Information conveyed through brain-control: cursor versus robot. IEEE Trans Neural Syst Rehabil Eng 2003;11:195-9.

Craelius W. The bionic man: restoring mobility. Science 2002;295:1018-21.

Paninski L, Fellows MR, Hatsopoulos NG, Donoghue JP. Spatio temporal tuning of motor cortical neurons for hand position and velocity. J. Neurophysiol 2004;91:515-32.

Karim A, Hinterberger T, Richter J, Melinger J, Neumann N, Flor H, et al. Neuronal internet: web surfing with brain potentials. Neurorehabil Neural Repair 2006;20:498-503.

Wolpaw J, Loeb G, Allison B, Donchin E, do Nascimento OF, Heetderks WJ, et al. ICC Meeting 2005 –Workshop on signals and recording methods. IEEE Trans Neural Syst Rehabil Eng 2006;14:138-42.

Lal TN, Schröder M, Hinterberger T, Weston J, Bogdan M, Birbaumer N, et al. Support vector channel selection in ICC. IEEE Trans Biomed Eng 2004;51:1003-10.

Leuthardt EC, Schalk G, Wolpaw JR, Ojemann JG, Moran DW. A brain–computer interface using electrocorticographic signals in humans. J Neural Eng 2004;1:63-71.

Mehring C, Rickert J, Vaadia E, Cardosa de Oliveira S, Aertsen A, Rotter S. Inference of hand movements from local field potentials in monkey motor cortex. Nat Neurosci 2003;6:1253-4.

Rickert J, Oliveira SC, Vaadia E, Aertsen A, Rotter S, Mehring C. Encoding of movement direction in different frequency ranges of motor cortical local field potentials. J Neurosci 2005;25:8815-24.

Donoghue JP, Nurmikko A, Black M, Hochberg LR. Assistive technology and robotic control using motor cortex ensemble-based neural interface systems in humans with tetraplegia. J Physiol 2007;579:603-11.

Dobkin BH. Brain-computer interface technology as a tool to augment plasticity and outcomes for neurological rehabilitation. J Physiol 2007;579:637-42.

Lebedev MA, Nicolelis MA. Brain-machine interfaces: past, present and future. Trends Neurosci 2006;29:53646.

Published

2009-12-31

How to Cite

Machado, S., Cunha, M., Velasques, B., Minc, D., Bastos, V. H., Budde, H., … Ribeiro, P. (2009). Brain computer-interface: new perspectives for rehabilitation. Revista Neurociências, 17(4), 329–235. https://doi.org/10.34024/rnc.2009.v17.8525

Issue

Section

Revisão de Literatura
##plugins.generic.dates.received## 2019-02-15
##plugins.generic.dates.published## 2009-12-31

Most read articles by the same author(s)

1 2 > >> 

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.