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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

286 related items for PubMed ID: 18575676

  • 1. Classification methods for ongoing EEG and MEG signals.
    Besserve M, Jerbi K, Laurent F, Baillet S, Martinerie J, Garnero L.
    Biol Res; 2007; 40(4):415-37. PubMed ID: 18575676
    [Abstract] [Full Text] [Related]

  • 2. Different classification techniques considering brain computer interface applications.
    Rezaei S, Tavakolian K, Nasrabadi AM, Setarehdan SK.
    J Neural Eng; 2006 Jun; 3(2):139-44. PubMed ID: 16705270
    [Abstract] [Full Text] [Related]

  • 3. Comparison of linear, nonlinear, and feature selection methods for EEG signal classification.
    Garrett D, Peterson DA, Anderson CW, Thaut MH.
    IEEE Trans Neural Syst Rehabil Eng; 2003 Jun; 11(2):141-4. PubMed ID: 12899257
    [Abstract] [Full Text] [Related]

  • 4. Neural network classification of autoregressive features from electroencephalogram signals for brain-computer interface design.
    Huan NJ, Palaniappan R.
    J Neural Eng; 2004 Sep; 1(3):142-50. PubMed ID: 15876633
    [Abstract] [Full Text] [Related]

  • 5. EEG-based motor imagery classification using neuro-fuzzy prediction and wavelet fractal features.
    Hsu WY.
    J Neurosci Methods; 2010 Jun 15; 189(2):295-302. PubMed ID: 20381529
    [Abstract] [Full Text] [Related]

  • 6. [Research on magnetoencephalography-brain computer interface based on the PCA and LDA data reduction].
    Wang J, Zhou L.
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2011 Dec 15; 28(6):1069-74. PubMed ID: 22295687
    [Abstract] [Full Text] [Related]

  • 7. BCI Competition 2003--Data set Ia: combining gamma-band power with slow cortical potentials to improve single-trial classification of electroencephalographic signals.
    Mensh BD, Werfel J, Seung HS.
    IEEE Trans Biomed Eng; 2004 Jun 15; 51(6):1052-6. PubMed ID: 15188877
    [Abstract] [Full Text] [Related]

  • 8. Plausibility assessment of a 2-state self-paced mental task-based BCI using the no-control performance analysis.
    Faradji F, Ward RK, Birch GE.
    J Neurosci Methods; 2009 Jun 15; 180(2):330-9. PubMed ID: 19439361
    [Abstract] [Full Text] [Related]

  • 9. Identification of the phase code in an EEG during gripping-force tasks: a possible alternative approach to the development of the brain-computer interfaces.
    Logar V, Skrjanc I, Belic A, Brezan S, Koritnik B, Zidar J.
    Artif Intell Med; 2008 Sep 15; 44(1):41-9. PubMed ID: 18657956
    [Abstract] [Full Text] [Related]

  • 10. Towards adaptive classification for BCI.
    Shenoy P, Krauledat M, Blankertz B, Rao RP, Müller KR.
    J Neural Eng; 2006 Mar 15; 3(1):R13-23. PubMed ID: 16510936
    [Abstract] [Full Text] [Related]

  • 11. Beyond mind-reading: multi-voxel pattern analysis of fMRI data.
    Norman KA, Polyn SM, Detre GJ, Haxby JV.
    Trends Cogn Sci; 2006 Sep 15; 10(9):424-30. PubMed ID: 16899397
    [Abstract] [Full Text] [Related]

  • 12. Classification of single MEG trials related to left and right index finger movements.
    Kauhanen L, Nykopp T, Sams M.
    Clin Neurophysiol; 2006 Feb 15; 117(2):430-9. PubMed ID: 16413826
    [Abstract] [Full Text] [Related]

  • 13. Which physiological components are more suitable for visual ERP based brain-computer interface? A preliminary MEG/EEG study.
    Bianchi L, Sami S, Hillebrand A, Fawcett IP, Quitadamo LR, Seri S.
    Brain Topogr; 2010 Jun 15; 23(2):180-5. PubMed ID: 20405196
    [Abstract] [Full Text] [Related]

  • 14. Decoding human motor activity from EEG single trials for a discrete two-dimensional cursor control.
    Huang D, Lin P, Fei DY, Chen X, Bai O.
    J Neural Eng; 2009 Aug 15; 6(4):046005. PubMed ID: 19556679
    [Abstract] [Full Text] [Related]

  • 15. Analyzing EEG signals using the probability estimating guarded neural classifier.
    Felzer T, Freisleben B.
    IEEE Trans Neural Syst Rehabil Eng; 2003 Dec 15; 11(4):361-71. PubMed ID: 14960111
    [Abstract] [Full Text] [Related]

  • 16. EEG and MEG brain-computer interface for tetraplegic patients.
    Kauhanen L, Nykopp T, Lehtonen J, Jylänki P, Heikkonen J, Rantanen P, Alaranta H, Sams M.
    IEEE Trans Neural Syst Rehabil Eng; 2006 Jun 15; 14(2):190-3. PubMed ID: 16792291
    [Abstract] [Full Text] [Related]

  • 17. xDAWN algorithm to enhance evoked potentials: application to brain-computer interface.
    Rivet B, Souloumiac A, Attina V, Gibert G.
    IEEE Trans Biomed Eng; 2009 Aug 15; 56(8):2035-43. PubMed ID: 19174332
    [Abstract] [Full Text] [Related]

  • 18. Fuzzy support vector machine for classification of EEG signals using wavelet-based features.
    Xu Q, Zhou H, Wang Y, Huang J.
    Med Eng Phys; 2009 Sep 15; 31(7):858-65. PubMed ID: 19487151
    [Abstract] [Full Text] [Related]

  • 19. Evolutionary optimization of classifiers and features for single-trial EEG discrimination.
    Aberg MC, Wessberg J.
    Biomed Eng Online; 2007 Aug 23; 6():32. PubMed ID: 17716370
    [Abstract] [Full Text] [Related]

  • 20. Entropy and complexity measures for EEG signal classification of schizophrenic and control participants.
    Sabeti M, Katebi S, Boostani R.
    Artif Intell Med; 2009 Nov 23; 47(3):263-74. PubMed ID: 19403281
    [Abstract] [Full Text] [Related]

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