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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

149 related items for PubMed ID: 10896181

  • 21. BCI Competition 2003--Data set III: probabilistic modeling of sensorimotor mu rhythms for classification of imaginary hand movements.
    Lemm S, Schäfer C, Curio G.
    IEEE Trans Biomed Eng; 2004 Jun; 51(6):1077-80. PubMed ID: 15188882
    [Abstract] [Full Text] [Related]

  • 22. [EEG-based communication--a new concept for rehabilitative support in patients with severe motor impairment].
    Neuper C, Müller GR, Staiger-Sälzer P, Skliris D, Kübler A, Birbaumer N, Pfurtscheller G.
    Rehabilitation (Stuttg); 2003 Dec; 42(6):371-7. PubMed ID: 14677109
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  • 23. Bipolar electrode selection for a motor imagery based brain-computer interface.
    Lou B, Hong B, Gao X, Gao S.
    J Neural Eng; 2008 Sep; 5(3):342-9. PubMed ID: 18756030
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  • 25. Extraction subject-specific motor imagery time-frequency patterns for single trial EEG classification.
    Ince NF, Tewfik AH, Arica S.
    Comput Biol Med; 2007 Apr; 37(4):499-508. PubMed ID: 17010962
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  • 27. EEG-based brain computer interface (BCI). Search for optimal electrode positions and frequency components.
    Pfurtscheller G, Flotzinger D, Pregenzer M, Wolpaw JR, McFarland D.
    Med Prog Technol; 2007 Apr; 21(3):111-21. PubMed ID: 8776708
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  • 28. A direct brain interface based on event-related potentials.
    Levine SP, Huggins JE, BeMent SL, Kushwaha RK, Schuh LA, Rohde MM, Passaro EA, Ross DA, Elisevich KV, Smith BJ.
    IEEE Trans Rehabil Eng; 2000 Jun; 8(2):180-5. PubMed ID: 10896180
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  • 29. Characterization of four-class motor imagery EEG data for the BCI-competition 2005.
    Schlögl A, Lee F, Bischof H, Pfurtscheller G.
    J Neural Eng; 2005 Dec; 2(4):L14-22. PubMed ID: 16317224
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  • 31. Toward a hybrid brain-computer interface based on imagined movement and visual attention.
    Allison BZ, Brunner C, Kaiser V, Müller-Putz GR, Neuper C, Pfurtscheller G.
    J Neural Eng; 2010 Apr; 7(2):26007. PubMed ID: 20332550
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  • 34. Exploring virtual environments with an EEG-based BCI through motor imagery.
    Leeb R, Scherer R, Keinrath C, Guger C, Pfurtscheller G.
    Biomed Tech (Berl); 2005 Apr; 50(4):86-91. PubMed ID: 15884704
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  • 35. The Berlin Brain-Computer Interface: EEG-based communication without subject training.
    Blankertz B, Dornhege G, Krauledat M, Müller KR, Kunzmann V, Losch F, Curio G.
    IEEE Trans Neural Syst Rehabil Eng; 2006 Jun; 14(2):147-52. PubMed ID: 16792281
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  • 38. Brain-computer interface research at the Neil Squire Foundation.
    Birch GE, Mason SG.
    IEEE Trans Rehabil Eng; 2000 Jun; 8(2):193-5. PubMed ID: 10896184
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  • 39. Using Actual and Imagined Walking Related Desynchronization Features in a BCI.
    Severens M, Perusquia-Hernandez M, Nienhuis B, Farquhar J, Duysens J.
    IEEE Trans Neural Syst Rehabil Eng; 2015 Sep; 23(5):877-86. PubMed ID: 26353236
    [Abstract] [Full Text] [Related]

  • 40. Significant improvement in one-dimensional cursor control using Laplacian electroencephalography over electroencephalography.
    Boudria Y, Feltane A, Besio W.
    J Neural Eng; 2014 Jun; 11(3):035014. PubMed ID: 24836436
    [Abstract] [Full Text] [Related]

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