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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

1065 related items for PubMed ID: 26822435

  • 21. Investigating the effects of visual distractors on the performance of a motor imagery brain-computer interface.
    Emami Z, Chau T.
    Clin Neurophysiol; 2018 Jun; 129(6):1268-1275. PubMed ID: 29677690
    [Abstract] [Full Text] [Related]

  • 22. Improving motor imagery through a mirror box for BCI users.
    Gómez DMC, Braidot AAA.
    J Neurophysiol; 2024 May 01; 131(5):832-841. PubMed ID: 38323330
    [Abstract] [Full Text] [Related]

  • 23. Effect of real-time cortical feedback in motor imagery-based mental practice training.
    Bai O, Huang D, Fei DY, Kunz R.
    NeuroRehabilitation; 2014 May 01; 34(2):355-63. PubMed ID: 24401829
    [Abstract] [Full Text] [Related]

  • 24. Motor imagery EEG classification based on ensemble support vector learning.
    Luo J, Gao X, Zhu X, Wang B, Lu N, Wang J.
    Comput Methods Programs Biomed; 2020 Sep 01; 193():105464. PubMed ID: 32283387
    [Abstract] [Full Text] [Related]

  • 25. Importance of baseline in event-related desynchronization during a combination task of motor imagery and motor observation.
    Tangwiriyasakul C, Verhagen R, van Putten MJ, Rutten WL.
    J Neural Eng; 2013 Apr 01; 10(2):026009. PubMed ID: 23428907
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  • 26. Lateralization patterns of covert but not overt movements change with age: An EEG neurofeedback study.
    Zich C, Debener S, De Vos M, Frerichs S, Maurer S, Kranczioch C.
    Neuroimage; 2015 Aug 01; 116():80-91. PubMed ID: 25979668
    [Abstract] [Full Text] [Related]

  • 27. Optimizing spatial patterns with sparse filter bands for motor-imagery based brain-computer interface.
    Zhang Y, Zhou G, Jin J, Wang X, Cichocki A.
    J Neurosci Methods; 2015 Nov 30; 255():85-91. PubMed ID: 26277421
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  • 28. Evaluation of feature extraction methods for EEG-based brain-computer interfaces in terms of robustness to slight changes in electrode locations.
    Park SA, Hwang HJ, Lim JH, Choi JH, Jung HK, Im CH.
    Med Biol Eng Comput; 2013 May 30; 51(5):571-9. PubMed ID: 23325145
    [Abstract] [Full Text] [Related]

  • 29. Improving motor imagery classification during induced motor perturbations.
    Vidaurre C, Jorajuría T, Ramos-Murguialday A, Müller KR, Gómez M, Nikulin VV.
    J Neural Eng; 2021 Jul 21; 18(4):. PubMed ID: 34233305
    [Abstract] [Full Text] [Related]

  • 30. Enhance decoding of pre-movement EEG patterns for brain-computer interfaces.
    Wang K, Xu M, Wang Y, Zhang S, Chen L, Ming D.
    J Neural Eng; 2020 Jan 24; 17(1):016033. PubMed ID: 31747642
    [Abstract] [Full Text] [Related]

  • 31. A hybrid BCI based on EEG and fNIRS signals improves the performance of decoding motor imagery of both force and speed of hand clenching.
    Yin X, Xu B, Jiang C, Fu Y, Wang Z, Li H, Shi G.
    J Neural Eng; 2015 Jun 24; 12(3):036004. PubMed ID: 25834118
    [Abstract] [Full Text] [Related]

  • 32. Electroencephalography (EEG)-based brain-computer interface (BCI): a 2-D virtual wheelchair control based on event-related desynchronization/synchronization and state control.
    Huang D, Qian K, Fei DY, Jia W, Chen X, Bai O.
    IEEE Trans Neural Syst Rehabil Eng; 2012 May 24; 20(3):379-88. PubMed ID: 22498703
    [Abstract] [Full Text] [Related]

  • 33. Real movement vs. motor imagery in healthy subjects.
    Höller Y, Bergmann J, Kronbichler M, Crone JS, Schmid EV, Thomschewski A, Butz K, Schütze V, Höller P, Trinka E.
    Int J Psychophysiol; 2013 Jan 24; 87(1):35-41. PubMed ID: 23123181
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  • 34. Decoding Multi-Class Motor Imagery From Unilateral Limbs Using EEG Signals.
    Rong F, Yang B, Guan C.
    IEEE Trans Neural Syst Rehabil Eng; 2024 Jan 24; 32():3399-3409. PubMed ID: 39236133
    [Abstract] [Full Text] [Related]

  • 35. A high performance sensorimotor beta rhythm-based brain-computer interface associated with human natural motor behavior.
    Bai O, Lin P, Vorbach S, Floeter MK, Hattori N, Hallett M.
    J Neural Eng; 2008 Mar 24; 5(1):24-35. PubMed ID: 18310808
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  • 36. Comparison of Brain Activation during Motor Imagery and Motor Movement Using fNIRS.
    Batula AM, Mark JA, Kim YE, Ayaz H.
    Comput Intell Neurosci; 2017 Mar 24; 2017():5491296. PubMed ID: 28546809
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  • 37. An EEG channel selection method for motor imagery based brain-computer interface and neurofeedback using Granger causality.
    Varsehi H, Firoozabadi SMP.
    Neural Netw; 2021 Jan 24; 133():193-206. PubMed ID: 33220643
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  • 38. Unraveling motor imagery brain patterns using explainable artificial intelligence based on Shapley values.
    Pérez-Velasco S, Marcos-Martínez D, Santamaría-Vázquez E, Martínez-Cagigal V, Moreno-Calderón S, Hornero R.
    Comput Methods Programs Biomed; 2024 Apr 24; 246():108048. PubMed ID: 38308997
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  • 39. Evidence of Variabilities in EEG Dynamics During Motor Imagery-Based Multiclass Brain-Computer Interface.
    Saha S, Ahmed KIU, Mostafa R, Hadjileontiadis L, Khandoker A.
    IEEE Trans Neural Syst Rehabil Eng; 2018 Feb 24; 26(2):371-382. PubMed ID: 29432108
    [Abstract] [Full Text] [Related]

  • 40. 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 24; 6(4):046005. PubMed ID: 19556679
    [Abstract] [Full Text] [Related]

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