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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

471 related items for PubMed ID: 24838215

  • 1. An independent SSVEP-based brain-computer interface in locked-in syndrome.
    Lesenfants D, Habbal D, Lugo Z, Lebeau M, Horki P, Amico E, Pokorny C, Gómez F, Soddu A, Müller-Putz G, Laureys S, Noirhomme Q.
    J Neural Eng; 2014 Jun; 11(3):035002. PubMed ID: 24838215
    [Abstract] [Full Text] [Related]

  • 2. Classification of binary intentions for individuals with impaired oculomotor function: 'eyes-closed' SSVEP-based brain-computer interface (BCI).
    Lim JH, Hwang HJ, Han CH, Jung KY, Im CH.
    J Neural Eng; 2013 Apr; 10(2):026021. PubMed ID: 23528484
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  • 3. Clinical feasibility of brain-computer interface based on steady-state visual evoked potential in patients with locked-in syndrome: Case studies.
    Hwang HJ, Han CH, Lim JH, Kim YW, Choi SI, An KO, Lee JH, Cha HS, Hyun Kim S, Im CH.
    Psychophysiology; 2017 Mar; 54(3):444-451. PubMed ID: 27914171
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  • 6. A hybrid BCI speller paradigm combining P300 potential and the SSVEP blocking feature.
    Xu M, Qi H, Wan B, Yin T, Liu Z, Ming D.
    J Neural Eng; 2013 Apr; 10(2):026001. PubMed ID: 23369924
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  • 9. Eliciting dual-frequency SSVEP using a hybrid SSVEP-P300 BCI.
    Chang MH, Lee JS, Heo J, Park KS.
    J Neurosci Methods; 2016 Jan 30; 258():104-13. PubMed ID: 26561770
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  • 11. Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface.
    Diez PF, Torres Müller SM, Mut VA, Laciar E, Avila E, Bastos-Filho TF, Sarcinelli-Filho M.
    Med Eng Phys; 2013 Aug 30; 35(8):1155-64. PubMed ID: 23339894
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  • 12. An Idle-State Detection Algorithm for SSVEP-Based Brain-Computer Interfaces Using a Maximum Evoked Response Spatial Filter.
    Zhang D, Huang B, Wu W, Li S.
    Int J Neural Syst; 2015 Nov 30; 25(7):1550030. PubMed ID: 26246229
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  • 14. Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain-computer interface.
    Chen X, Wang Y, Gao S, Jung TP, Gao X.
    J Neural Eng; 2015 Aug 30; 12(4):046008. PubMed ID: 26035476
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  • 15. Frequency recognition in an SSVEP-based brain computer interface using empirical mode decomposition and refined generalized zero-crossing.
    Wu CH, Chang HC, Lee PL, Li KS, Sie JJ, Sun CW, Yang CY, Li PH, Deng HT, Shyu KK.
    J Neurosci Methods; 2011 Mar 15; 196(1):170-81. PubMed ID: 21194547
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  • 16. A practical, intuitive brain-computer interface for communicating 'yes' or 'no' by listening.
    Hill NJ, Ricci E, Haider S, McCane LM, Heckman S, Wolpaw JR, Vaughan TM.
    J Neural Eng; 2014 Jun 15; 11(3):035003. PubMed ID: 24838278
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  • 17. Brain-computer interfaces for 1-D and 2-D cursor control: designs using volitional control of the EEG spectrum or steady-state visual evoked potentials.
    Trejo LJ, Rosipal R, Matthews B.
    IEEE Trans Neural Syst Rehabil Eng; 2006 Jun 15; 14(2):225-9. PubMed ID: 16792300
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  • 19. Probing command following in patients with disorders of consciousness using a brain-computer interface.
    Lulé D, Noirhomme Q, Kleih SC, Chatelle C, Halder S, Demertzi A, Bruno MA, Gosseries O, Vanhaudenhuyse A, Schnakers C, Thonnard M, Soddu A, Kübler A, Laureys S.
    Clin Neurophysiol; 2013 Jan 15; 124(1):101-6. PubMed ID: 22920562
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  • 20. An independent brain-computer interface using covert non-spatial visual selective attention.
    Zhang D, Maye A, Gao X, Hong B, Engel AK, Gao S.
    J Neural Eng; 2010 Feb 15; 7(1):16010. PubMed ID: 20083864
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