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Brain-Machine Interfaces

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Encyclopedia of Robotics
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Synonyms

Brain-computer interface (BCI), Mind-machine interface (MMI),Direct neural interface (DNI)

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References

  • Amiri S, Fazel-Rezai R, Asadpour V (2013) A review of hybrid brain-computer interface systems. Adv Hum Comput Interact 2013:1–8

    Article  Google Scholar 

  • Bouton CE, Shaikhouni A, Annetta NV, Bockbrader MA, Friedenberg DA, Nielson DM, Morgan AG (2016) Restoring cortical control of functional movement in a human with quadriplegia. Nature 533:247–250

    Article  Google Scholar 

  • Carelli L, Solca F, Faini A, Meriggi P, Sangalli D, Cipresso P, Riva G, Ticozzi N, Ciammola A, Silani V, Poletti B (2017) Brain-computer interface for clinical purposes: cognitive assessment and rehabilitation. BioMed Res Int 2017:1695290

    Article  Google Scholar 

  • Chatterjee A, Aggarwal V, Ramos A, Acharya S, Thakor NV (2007) A brain-computer interface with vibrotactile biofeedback for haptic information. J Neuroeng Rehabil 4:40

    Article  Google Scholar 

  • Chaudhary U, Birbaumer N, Ramos-Murguialday A (2016) Brain-computer interfaces for communication and rehabilitation. Nature Rev Neurol 12:513–525

    Article  Google Scholar 

  • Chen X, Wang Y, Nakanishi M, Gao X, Jung TP, Gao S (2015) High-speed spelling with a noninvasive brain–computer interface. Proc Natl Acad Sci U S A 112:E6058–E6067

    Article  Google Scholar 

  • Collinger JL, Wodlinger B, Downey JE, Wang W, Tyler-Kabara EC, Weber DJ, Schwartz AB (2013) High-performance neuroprosthetic control by an individual with tetraplegia. The Lancet 381:557–564

    Article  Google Scholar 

  • De Vos M, Kroesen M, Emkes R, Debener S (2014) P300 speller BCI with a mobile EEG system: comparison to a traditional amplifier. J Neural Eng 11:036008

    Article  Google Scholar 

  • Fazel-Rezai R, Allison BZ, Guger C, Sellers EW, Kleih SC, Kübler A (2012) P300 brain computer interface: current challenges and emerging trends. Front Neuroeng 5:14

    Article  Google Scholar 

  • Han CH, Hwang HJ, Lim JH, Im CH (2018) Assessment of user voluntary engagement during neurorehabilitation using functional near-infrared spectroscopy: a preliminary study. J Neuroeng Rehabil. in press

    Google Scholar 

  • Hochberg LR, Serruya MD, Friehs GM, Mukand JA, Saleh M, Caplan AH, Donoghue JP (2006) Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 442:164–171

    Article  Google Scholar 

  • Hochberg LR, Bacher D, Jarosiewicz B, Masse NY, Simeral JD, Vogel J, Donoghue JP (2012) Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature 485:372–375

    Article  Google Scholar 

  • Hwang HJ, Kwon K, Im CH (2009) Neurofeedback-based motor imagery training for brain–computer interface (BCI). J Neurosci Methods 179:150–156

    Article  Google Scholar 

  • Hwang HJ, Kim S, Choi S, Im CH (2013) EEG-based brain-computer interfaces: a thorough literature survey. Int J Hum Comput Interact 29:814–826

    Article  Google Scholar 

  • Hwang HJ, Lim JH, Kim DW, Im CH (2014) Evaluation of various mental task combinations for near-infrared spectroscopy-based brain-computer interfaces. J Biomed Opt 19:77005

    Article  Google Scholar 

  • Hwang HJ, Han CH, Lim JH, Kim YW, Choi SI, An KO, Im CH (2017) Clinical feasibility of brain-computer interface based on steady-state visual evoked potential in patients with locked-in syndrome: case studies. Psychophysiology 54:444–451

    Article  Google Scholar 

  • Kim DW, Hwang HJ, Lim JH, Lee YH, Jung KY, Im CH (2011) Classification of selective attention to auditory stimuli: toward vision-free brain–computer interfacing. J Neurosci Methods 197:180–185

    Article  Google Scholar 

  • Liao LD, Chen CY, Wang IJ, Chen SF, Li SY, Chen BW, Lin CT (2012) Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors. J Neuroeng Rehabil 9:5

    Article  Google Scholar 

  • Lotte F, Congedo M, Lécuyer A, Lamarche F, Arnaldi B (2007) A review of classification algorithms for EEG-based brain–computer interfaces. J Neural Eng 4:R1–R13

    Article  Google Scholar 

  • McCreadie KA, Coyle DH, Prasad G (2013) Sensorimotor learning with stereo auditory feedback for a brain-computer interface. Med Biol Eng Comput 51:285

    Article  Google Scholar 

  • Mellinger J, Schalk G, Braun C, Preissl H, Rosenstiel W, Birbaumer N, Kübler A (2007) An MEG-based brain–computer interface (BCI). Neuroimage 36:581–593

    Article  Google Scholar 

  • Muller-Putz GR, Scherer R, Neuper C, Pfurtscheller G (2006) Steady-state somatosensory evoked potentials: suitable brain signals for brain-computer interfaces? IEEE Trans Neural Syst Rehabil Eng 14:30–37

    Article  Google Scholar 

  • Naseer N, Hong KS (2015) fNIRS-based brain-computer interfaces: a review. Front Hum Neurosci 9:172

    Google Scholar 

  • Nicolas-Alonso LF, Gomez-Gil J (2012) Brain computer interfaces, a review. Sensors 12:1211–1279

    Article  Google Scholar 

  • Park W, Kwon GH, Kim DH, Kim YH, Kim SP, Kim L (2014) Assessment of cognitive engagement in stroke patients from single-trial EEG during motor rehabilitation. IEEE Trans Neural Syst Rehabil Eng 23:351–362

    Google Scholar 

  • Schalk G, Leuthardt EC (2011) Brain-computer interfaces using electrocorticographic signals. IEEE Rev Biomed Eng 4:140–154

    Article  Google Scholar 

  • Silvoni S, Ramos-Murguialday A, Cavinato M, Volpato C, Cisotto G, Turolla A, Piccione F, Birbaumer N (2011) Brain-computer interface in stroke: a review of progress. Clin EEG Neurosci 42:245–252

    Article  Google Scholar 

  • Sitaram R, Caria VR, Gaber T, Rota G, Kuebler A, Birbaumer N (2007) FMRI brain-computer interface: a tool for neuroscientific research and treatment. Comput Intell Neurosci 2007:1–10

    Article  Google Scholar 

  • Tidoni E, Gergondet P, Kheddar A, Aglioti SM (2014) Audio-visual feedback improves the BCI performance in the navigational control of a humanoid robot. Front Neurorobot 8:20

    Article  Google Scholar 

  • Vargas-Irwin CE, Shakhnarovich G, Yadollahpour P, Mislow JM, Black MJ, Donoghue JP (2010) Decoding complete reach and grasp actions from local primary motor cortex populations. J Neurosci 30:9659–9669

    Article  Google Scholar 

  • Velliste M, Perel S, Spalding MC, Whitford AS, Schwartz AB (2008) Cortical control of a prosthetic arm for self-feeding. Nature 453:1098–1101

    Article  Google Scholar 

  • Vidal JJ (1973) Toward direct brain-computer communication. Annu Rev Biophys Bioeng 2:157–180

    Article  Google Scholar 

  • Vidaurre C, Schlogl A, Cabeza R, Scherer R, Pfurtscheller G (2006) A fully on-line adaptive BCI. IEEE Trans Biomed Eng 53:1214–1219

    Article  Google Scholar 

  • Volosyak I (2011) SSVEP-based Bremen–BCI interface—boosting information transfer rates. J Neural Eng 8:036020

    Article  Google Scholar 

  • Wessberg J, Stambaugh CR, Kralik JD, Beck PD, Laubach M, Chapin JK, Nicolelis MA (2000) Real-time prediction of hand trajectory by ensembles of cortical neurons in primates. Nature 408:361–365

    Article  Google Scholar 

  • Zander TO, Kothe C (2011) Towards passive brain–computer interfaces: applying brain–computer interface technology to human–machine systems in general. J Neural Eng 8:025005

    Article  Google Scholar 

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Correspondence to Chang-Hwan Im .

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Im, CH. (2019). Brain-Machine Interfaces. In: Ang, M., Khatib, O., Siciliano, B. (eds) Encyclopedia of Robotics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41610-1_23-1

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  • DOI: https://doi.org/10.1007/978-3-642-41610-1_23-1

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  • Print ISBN: 978-3-642-41610-1

  • Online ISBN: 978-3-642-41610-1

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