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뇌파 기반 뇌-컴퓨터 인터페이스 기술의 소개
Introduction to EEG-Based Brain-Computer Interface (BCI) Technology 원문보기

Journal of biomedical engineering research : the official journal of the Korean Society of Medical & Biological Engineering, v.31 no.1, 2010년, pp.1 - 13  

임창환 (연세대학교 의공학부)

Abstract AI-Helper 아이콘AI-Helper

There are a great numbers of disabled individuals who cannot freely move or control specific parts of their body because of serious neurological diseases such as spinal cord injury, amyotrophic lateral sclerosis, brainstem stroke, and so on. Brain-computer interfaces (BCIs) can help them to drive an...

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참고문헌 (87)

  1. C.J.L. Murray, A.D. Lopez, The global burden of disease: a comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 projected to 2020, Harvard University Press, 1996. 

  2. G.T. Carter, "Rehabilitation management in neuromuscular disease," J. Neurol. Rehabil., vol. 11, pp. 69-80, 1997. 

  3. J.J. Vidal, "Towards direct brain-computer communication," Annu. Rev. Biophys. Bioeng., vol. 2, pp. 157-180, 1973. 

  4. L.R. Hochberg, M.D. Serruya, G.M. Friehs, et al., "Neuronal ensemble control of prosthetic devices by a human with tetraplegia," Nature, vol. 442, pp. 164-171, 2006. 

  5. S. Musallam, B.D. Corneil, B. Greger, H. Scherberger, and R.A. Andersen, "Cognitive control signals for neural prosthetics," Science, vol. 305, pp. 258-268, 2004. 

  6. J.M. Carmena, M.A. Lebedev, R.E. Crist, et al., "Learning to control a brain-machine interface for reaching and grasping by primates," PLoS Biol., vol. 1, E42, 2003. 

  7. E.C. Leuthardt, G. Schalk, J.R. Wolpaw, J.G. Ojemann, and D.W. Moran, "A brain-computer interface using electrocorticographic signals in humans," J. Neural Eng., vol. 1, pp. 63-71, 2004. 

  8. G. Schalk, K.J. Miller, N.R. Anderson, et al., "Two-dimensional movement control using electrocorticographic signals in humans," J. Neural Eng., vol. 5, pp. 75-84, 2008. 

  9. T. Stieglitz, B. Rubehn, C. Henle, S. Kisban, S. Herwik, P. Ruther, and M. Schuettler, "Brain-computer interfaces: an overview of the hardware to record neural signals form the cortex," Prog. Brain Res., vol. 175, pp. 297-315, 2009. 

  10. G. Dornhege, J.R. Millan, T. Hinterberger, D.J. McFarland, and K.R. Muller, Toward Brain-Computer Interfacing, The MIT Press, 2007. 

  11. J.R. Wolpaw, N. Birbaumer, D.J. McFarland, G. Pfurtscheller, and T.M. Vaughana, "Brain-computer interfaces for communication and control," Clin. Neurophysiol., vol. 113, pp. 767-791, 2002. 

  12. G. Pfurtscheller and C. Neuper, "Motor imagery activates primary sensorimotor area in humans," Neurosci. Lett., vol. 239, pp.65-68, 1997. 

  13. G. Pfurtscheller and C. Neuper, "Motor imagery and direct brain-computer communication," Proc. IEEE, vol. 89, pp. 1123-1134, 2001. 

  14. J.J. Daly and J.R. Wolpaw, "Brain-computer interfaces in neurological rehabilitation," Lancet Neurol., vol. 7, pp. 1032-1043, 2008. 

  15. C. Neuper, R. Scherer, M. Reiner, G. Pfurtscheller, "Imagery ofmotor actions: differential effects of kinesthetic and visual-motor mode of imagery in single-trial EEG," Cogn. Brain Res., vol. 25, pp. 668-677, 2005. 

  16. C.R. Hall and K.A. Kathleen, "Measuring movement imagery abilities: A revision of the Movement Imagery Questionnaire," J. Mental Imag., vol. 21, pp. 143-154, 1997. 

  17. H.J. Hwang, K. Kwon, and C.H. Im, "Neurofeedback-Based Motor Imagery Training for Brain-Computer Interface (BCI)," J. Neurosci. Meth., vol. 179, no. 1, pp. 150-156, 2009. 

  18. T. Wang, J. Deng, and B. He, "Classifying EEG-based motor imagery tasks by means of time-frequency synthesized spatial patterns," Clin. Neurophysiol., vol. 115, pp. 2744-2753, 2004. 

  19. N.F. Ince, S. Arica, and A. Tewfik, "Classification of single trial motor imagery EEG recordings with subject adapted non-dyadic arbitrary time-frequency tilings," J. Neural Eng., vol. 3, pp. 235-244, 2006. 

  20. B. Kamousi, A.N. Amini, and B. He, "Classification of motor imagery by means of cortical current density estimation and Von Neumann entropy," J. Neural Eng., vol. 4, pp. 17-25, 2007. 

  21. G. Pfurtscheller and T. Solis-Escalante, "Could the beta rebound in the EEG be suitable to realize a "brain switch?" Clin. Neurophysiol., vol. 120, pp. 24-29, 2009. 

  22. G. Pfurtscheller and F.H. Lopes da Silva, "Event-related EEG/MEG synchronization and desynchronization: basic principles," Clin. Neurophysiol., vol. 110, pp. 1842-1857, 1999. 

  23. K.H. Kim, J.H. Kim, J. Yoon, K.Y. Jung, "Influence of task difficulty on the features of event-related potential during visual oddball task," Neurosci. Lett., vol. 445, pp. 179-183, 2008. 

  24. E.W. Sellers, A. Kubler, and E. Donchin, "Brain-computer interface research at the University of South Florida Cognitive Psychophysiology Laboratory: the P300 Speller," IEEE Trans. Neural. Syst. Rehabil. Eng., vol. 14, pp. 221-224, 2006. 

  25. E. Donchin, K.M. Spencer, and R. Wijesinghe, "The mental prosthesis: assessing the speed of a P300-based brain-computer interface," IEEE Trans. Neural. Syst. Rehabil. Eng., vol. 8, pp. 174-179, 2000. 

  26. H. Serby, E. Yom-Tov, and G.F. Inbar, "An improved P300-based braincomputer interface," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 13, pp. 89-98, 2005. 

  27. A. Lenhardt, M. Kaper, and H.J. Ritter, "An adaptive P300-based online brain-computer interface," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 16, pp. 121-130, 2008. 

  28. M. Middendorf, G. McMillan, G. Calhoun, and K.S. Jones, "Brain-Computer Interfaces Based on the Steady-State Visual-Evoked Response," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 8, pp. 211-214, 2000. 

  29. M. Cheng, X. Gao, S. Gao, and D. Xu, "Design and implementation of a brain-computer interface with high transfer rates," IEEE Trans.Biomed. Eng., vol. 10, pp. 1181-1186, 2002. 

  30. G. R. Muller-Putz, R. Scherer, C. Brauneis, and G. Pfurtscheller, "Steady-state visual evoked potential (SSVEP)-Based communication: Impact of harmonic frequency components," J. Neural Eng., vol. 2, pp. 123-130, 2005. 

  31. Y. Wang, R. Wang, X. Gao, B. Hong, and S. Gao, "A Practical VEP-Based Brain-Computer Interface," IEEE Trans. Biomed. Eng., vol. 14, no. 2, 2006. 

  32. Z. Wu, Y. Lai, Y. Xia, D. Wu, and D. Yao, "Stimulator selection in SSVEP-based BCI," Med. Eng. Phys., vol. 30, pp. 1079-1088, 2008. 

  33. E. E. Sutter, "The brain response interface: Communication through visually-induced electrical brain response," J. Microcomput. Applicat., vol. 15, pp. 31-45, 1992. 

  34. A. Kubler, N. Neumann, J. Kaiser, B. Kotchoubey, T. Hinterberger, and N.P. Birbaumer, "Brain-computer communication: self-regulation of slow cortical potentials for verbal communication," Arch. Phys. Med. Rehabil., vol. 82, pp. 1533-1539, 2001. 

  35. N. Birbaumer, A. Kubler, N. Ghanayim, et al., "The thought translation device (TTD) for completely paralyzed patients," IEEE Trans. Rehabil. Eng., vol. 8, pp. 190-193, 2000. 

  36. N. Birbaumer, N. Ghanayim, T. Hinterberger, et al., "A spelling device for the paralysed," Nature vol. 398, pp. 297-298, 1999. 

  37. J. Perelmouter and N. Birbaumer, "A binary spelling interface with random errors," IEEE Trans. Rehabil. Eng., vol. 8, pp. 227-232, 2000. 

  38. F. Nijboer, A. Furdea, I. Gunst, et al., "An auditory brain-computer interface (BCI)," J Neurosci. Meth., vol. 167, pp. 43-50, 2008. 

  39. C. Petitot, L. Collet, and J.D. Durrant, "Auditory steady-state responses (ASSR): effects of modulation and carrier frequencies," Int. J. Audiol., vol. 44, pp. 567-573, 2005. 

  40. P. Desain, J. Farquhar, J. Blankespoor, and S. Gielen, "Detecting spread spectrum pseudo random noise tags in EEG/MEG using a structure-based decomposition," Proc. 4th Int. BCI Workshop and Training Course, Graz, Austria, 2008. 

  41. A. Furdea, S. Halder, D.J. Krusienski, D. Bross, F. Nijboer, N. Birbaumer, and A. Jubler, "An auditory oddball (P300) spelling system for brain-computer interfaces," Psychophysiol., vol. 46, pp. 617-625, 2009. 

  42. S. Kanoh, K. Miyamoto, and T. Yoshinobu, "A Brain-Computer Interface (BCI) System Based on Auditory Stream Segregation," Proc. 30th Ann. Int. Conf. IEEE EMBS, Vancouver, Canada, 2008. 

  43. N.J. Hill, T. N. Lal, K. Bierig, N. Birbaumer, and B. Scholkopf, "An Auditory Paradigm for Brain-Computer Interfaces," Adv. Neural Infom. Process. Syst., vol. 17, pp. 569-576, 2005. 

  44. N.J. Hill et al., "Attentional modulation of auditory event-related potentials in a brain-computer interface," Proc. 2004 IEEE International workshop on Biomedical Circuits and Systems, pp S3.5.INV-17-20, 2004. 

  45. D.W. Kim, H.J. Hwang, J.H. Lim, and C.H. Im, "Classification of selective attention to auditory stimuli with different beat frequencies and directions: a preliminary study," Proc. TOBI Workshop 2010, Graz, Austria, 2010 (Journal paper in preparation). 

  46. R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification (2/E), Wiley, 2000. 

  47. M. Pregenzer, G. Pfurtscheller, and D. Flotzinger, "Selection of electrode positions for an EEG-based Brain Computer Interface (BCI), Biomedizinische Technik, vol. 39, pp. 264-269, 1994. 

  48. D.J. McFarland, L.M. McCane, S.V. David, and J.R. Wolpaw, "Spatial filter selection for EEG-based communication," Electroencephalogr. Clin. Neurophysiol., vol. 103, pp. 386-394, 1997. 

  49. G. Pfurtscheller and C. Neuper, "Motor imagery and direct brain-computer communication," Proc. IEEE, vol. 89, pp. 1123-1134, July 2001. 

  50. W. Penny, S. Roberts, and M. Stokes, "Imagined hand movements identified from the EEG mu-rhythm," Dept. Elect. Eng., Imperial College, London, U.K., Tech. Rep., 1998. 

  51. C. Anderson, E. Stolz, and S. Shamsunder, "Discriminating mental tasks using EEG represented by AR models," in Proc. IEEE Engineering in Medicine and Biology Annu. Conf, Sept. 1995. 

  52. A. Schlogl, G. Pfurtscheller, and B. Schack, "Single-trial EEG analysis using an adaptive autoregressive model," in Proc. 4th Int. Symp. Central Nervous Monitoring, Sept. 1996. 

  53. E. Curran, P. Sykacek, S. Roberts, W. Penny, M. Stokes, I. Johnsrude, and A. Owen, "Cognitive tasks for driving a brain computer interfacing system: a pilot study," IEEE Trans. Neural Syst. Rehab. Eng., vol. 12, pp. 48-54, Mar. 2004. 

  54. S. Roberts, W. Penny, and I. Rezek, "Temporal and spatial complexity measures for EEG-based brain-computer interfacing," Med. Biol. Eng. Comput., vol. 37, no. 1, pp. 93-99, 1998. 

  55. C. Guger, H. Ramoser, and G. Pfurtscheller, "Real-time EEG analysis with subject-specific spatial patterns for a brain-computer interface," IEEE Trans. Rehab. Eng., vol. 8, pp. 447-456, Dec. 2000. 

  56. N. Yamawaki, C. Wilke, Z. Liu, and B. He, "An enhanced time-frequency approach for motor imagery classification," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 14, pp. 250-254, 2006. 

  57. E. Gysels and P. Celka, "Phase Synchronization for the Recognition of Mental Tasks in a Brain-Computer Interface," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 12, pp. 406-415, 2004. 

  58. C. Brunner, R. Scherer, B. Graimann, G. Supp, and G. Pfurtscheller, "Online Control of a Brain-Computer Interface Using Phase Synchronization," IEEE Trans. Biomed. Eng., vol. 53, pp. 2501-2506, 2006. 

  59. Q. Wei, Y. Wang, X. Gao, and S. Gao, "Amplitude and phase coupling measures for feature extraction in an EEG-based brain-computer interface," J. Neural Eng., vol. 4, pp. 120-129, 2007. 

  60. F. Lotte, M. Congedo, A. Lecuyer, F. Lamarche, and B. Arnaldi, "A review of classification algorithms for EEG-based brain-computer interfaces," J. Neural Eng., vol. 4, pp. R1-R13, 2007. 

  61. G.E. Fabiani, D.J. McFarland, J.R. Wolpaw, and G. Pfurtscheller, "Conversion of EEG activity into cursor movement by a brain-computer interface (BCI)," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 12, pp. 331-338, 2004. 

  62. D.J. Krusienski, E.W. Seller, D.J. McFarland, T.M. Vaughan, and J.R. Wolpaw, "Toward enhanced P300 speller performance," J. of Neurosci. Meth., vol. 167, pp.15-21, 2008. 

  63. S. Inoue, Y. Akiyama, Y. Izumi, and S. Nishijima, "The development of BCI using alpha waves for controlling the robot arm," Ieice Transactions On Communications, vol. E91B, pp. 2125-2132, 2008. 

  64. A. Sonar, J. Carroll, G. Fulk, C. Wood, and J. Searleman, "Development of a virtual reality-based power wheelchair simulator, " Cyberpsychol., vol. 9, pp. 718-719. 2006. 

  65. Q. Liu, X. Zhao, B. Wan, L. Zhao, "Remote control system of an electric car based on the alpha waves in EEG," Proc. World Congress on Intelligent Control and Automation (WCICA), art. no. 1713824, pp. 9416-9420, 2006. 

  66. N, Birbaumer, "Breaking the silence: Brain-computer interfaces (BCI) for communication and motor control," Psychophsiol., vol. 43, pp. 517-532, 2006. 

  67. G. Pfurtscheller, G.R. Muller-Putz, J. Pfurtscheller, and R. Rupp, "EEG-Based Asynchronous BCI Controls Functional Electrical Stimulation in a Tetraplegic Patient," Eurasip J. Appl. Sig. Process., pp. 3152-3155, 2005. 

  68. A. Nijholt, D. Plass-Oude Bos, and B. Reuderink, "Turning shortcomings into challenges: Brain-computer interfaces for games," Ent. Compt., vol. 1, pp. 85-94, 2009. 

  69. N. J. Hill, T. N. Lal, M. Schroder, et al., "Classifying EEG and ECoG Signals without Subject Training for Fast BCI Implementation: Comparison of Non-Paralysed and Completely Paralysed Subjects," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 14, pp. 183-186, 2006. 

  70. A. Buttfield, P. W. Ferrez, and J. del R. Millan, "Towards a robust BCI: Error potentials and online learning," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 14, pp. 164-168, 2006. 

  71. J. F. Borisoff, S. G. Mason, and G. E. Birch, "Brain Interface Research for Asynchronous Control Applications," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 14, pp. 160-163, 2006. 

  72. A. Bashashati, S. mason, R.K. Ward, and G.E. Birch, "An improved asynchronous brain interface: making use of the temporal history of the LF-ASD feature vectors," J. Neural Eng., vol. 3, pp. 87-94, 2006. 

  73. R. Scherer, G.R. Muller, C. Neuper, B. Graimann, and G. Pfurtscheller, "An Asynchronously Controlled EEG-Based Virtual Keyboard: Improvement of the Spelling Rate," IEEE Trans. Biomed. Eng., vol. 51, pp. 979-984, 2004. 

  74. A. Ishikawa, S. Shiomi, S. Kohno, H. Udagawa, S. Tsuneisi, T. Amita, and Y. Mukuta, "NIRSEEGFusion: Implementation fusion software for functional NIRS and EEG data on anatomical MRI data," NeuroImage, vol. 47, Suppl. 1, pp. S140, 2009. 

  75. C.H. Im, Z. Liu, N. Zhang, W. Chen, and Bin He, "Functional Cortical Source Imaging from Simultaneously Recorded ERP and fMRI," J. Neurosci. Meth., vol. 157, no. 1, pp. 118-123, 2006. 

  76. G. Pfurtscheller, "The Hybrid BCI," Proc. BBCI Workshop 2009, Berlin, Germany, 2009. 

  77. D. Huang, P. Lin, D.Y. Fei, X. Chen, and O. Bai, "Decoding human motor activity from EEG single trials for a discrete two-dimensional cursor control," J. Neural Eng., vol. 6, 046005, 2009. 

  78. D. Zhang, A. Maye, X. Gao, B. Hong, A.K. Engel, and S. Gao, "An independent brain-computer interface using covert non-spatial visual selective attention," J. Neural Eng., vol. 7, 016010, 2010. 

  79. K. Jerbi, J.P. Lachaux, K. N'Diaye, D. Pantazis, R.M. Leahy, L. Garnero, and S. Baillet, "Neural representation of hand speed in humans revealed by MEG imaging," Proc. Nat. Acad. Sci. USA vol. 104, pp. 7676-7681, 2007. 

  80. F. Faradji, R.K. Ward, and G.E. Birch, "Plausibility assessment of a 2-state self-paced mental task-based BCI using the no-control performance analysis," J. Neurosci. Meth., vol. 180, pp. 330-339, 2009. 

  81. L. Qin, L. Ding, and B. He, "Motor imagery classification by means of source analysis for brain-computer interface applications," J. Neural Eng., vol. 1, 135, 2004. 

  82. B. Kamousi, Z. Liu, and B. He, "Classification of Motor Imagery Tasks for Brain-Computer Interface Applications by Means of Two Equivalent Dipoles Analysis," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 13, pp. 166-171, 2005. 

  83. Q. Noirhomme, R.I. Kitney,and B. Macq, "Single-Trial EEG Source Reconstruction for Brain-Computer Interface," IEEE Trans. Biomed. Eng., vol. 55, pp. 1592-1601, 2008. 

  84. M. Congedo, F. Lotte, and A. Lecuyer, "Classification of movement intention by spatially filtered electromagnetic inverse solutions," Phys. Med. Biol., vol. 51, 1971, 2006. 

  85. R.C. deCharms, "Applications of real-time fMRI," Nat. Rev. Neurosci., vol. 9, pp. 720-729. 

  86. C.H. Im, H.J. Hwang, H. Che, and S. Lee, "An EEG-based Real-time Cortical Rhythmic Activity Monitoring System," Physiol. Meas., vol. 28, pp. 1101-1113, 2007. 

  87. C.H. Im and H.J. Hwang, "EEG-based Real-time Dynamic Neuroimaging," Proc. 31st Ann. Int. Conf. IEEE EMBS, Minneapolis, USA, 2009 (journal paper in preparation). 

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