These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

152 related articles for article (PubMed ID: 22255362)

  • 1. A subject-independent brain-computer interface based on smoothed, second-order baselining.
    Reuderink B; Farquhar J; Poel M; Nijholt A
    Annu Int Conf IEEE Eng Med Biol Soc; 2011; 2011():4600-4. PubMed ID: 22255362
    [TBL] [Abstract][Full Text] [Related]  

  • 2. The non-invasive Berlin Brain-Computer Interface: fast acquisition of effective performance in untrained subjects.
    Blankertz B; Dornhege G; Krauledat M; Müller KR; Curio G
    Neuroimage; 2007 Aug; 37(2):539-50. PubMed ID: 17475513
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine-learning-based coadaptive calibration for brain-computer interfaces.
    Vidaurre C; Sannelli C; Müller KR; Blankertz B
    Neural Comput; 2011 Mar; 23(3):791-816. PubMed ID: 21162666
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Comparison of designs towards a subject-independent brain-computer interface based on motor imagery.
    Lotte F; Guan C; Ang KK
    Annu Int Conf IEEE Eng Med Biol Soc; 2009; 2009():4543-6. PubMed ID: 19964647
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Calibrating EEG-based motor imagery brain-computer interface from passive movement.
    Ang KK; Guan C; Wang C; Phua KS; Tan AH; Chin ZY
    Annu Int Conf IEEE Eng Med Biol Soc; 2011; 2011():4199-202. PubMed ID: 22255265
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Subject Separation Network for Reducing Calibration Time of MI-Based BCI.
    Hu H; Yue K; Guo M; Lu K; Liu Y
    Brain Sci; 2023 Jan; 13(2):. PubMed ID: 36831764
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Neural mechanisms of brain-computer interface control.
    Halder S; Agorastos D; Veit R; Hammer EM; Lee S; Varkuti B; Bogdan M; Rosenstiel W; Birbaumer N; Kübler A
    Neuroimage; 2011 Apr; 55(4):1779-90. PubMed ID: 21256234
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Integrating dynamic stopping, transfer learning and language models in an adaptive zero-training ERP speller.
    Kindermans PJ; Tangermann M; Müller KR; Schrauwen B
    J Neural Eng; 2014 Jun; 11(3):035005. PubMed ID: 24834896
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Common spatial pattern patches - an optimized filter ensemble for adaptive brain-computer interfaces.
    Sannelli C; Vidaurre C; Muller KR; Blankertz B
    Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():4351-4. PubMed ID: 21096003
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Classification of electroencephalogram signals using wavelet-CSP and projection extreme learning machine.
    Dai Y; Zhang X; Chen Z; Xu X
    Rev Sci Instrum; 2018 Jul; 89(7):074302. PubMed ID: 30068128
    [TBL] [Abstract][Full Text] [Related]  

  • 11. An approach to improve the performance of subject-independent BCIs-based on motor imagery allocating subjects by gender.
    Cantillo-Negrete J; Gutierrez-Martinez J; Carino-Escobar RI; Carrillo-Mora P; Elias-Vinas D
    Biomed Eng Online; 2014 Dec; 13():158. PubMed ID: 25476924
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Large-Scale Assessment of a Fully Automatic Co-Adaptive Motor Imagery-Based Brain Computer Interface.
    Acqualagna L; Botrel L; Vidaurre C; Kübler A; Blankertz B
    PLoS One; 2016; 11(2):e0148886. PubMed ID: 26891350
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Subject-to-subject adaptation to reduce calibration time in motor imagery-based brain-computer interface.
    Arvaneh M; Robertson I; Ward TE
    Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():6501-4. PubMed ID: 25571485
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Multisubject learning for common spatial patterns in motor-imagery BCI.
    Devlaminck D; Wyns B; Grosse-Wentrup M; Otte G; Santens P
    Comput Intell Neurosci; 2011; 2011():217987. PubMed ID: 22007194
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Subject-to-subject transfer for CSP based BCIs: feature space transformation and decision-level fusion.
    Heger D; Putze F; Herff C; Schultz T
    Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():5614-7. PubMed ID: 24111010
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Minimizing calibration time using inter-subject information of single-trial recognition of error potentials in brain-computer interfaces.
    Iturrate I; Montesano L; Chavarriaga R; del R Millán J; Minguez J
    Annu Int Conf IEEE Eng Med Biol Soc; 2011; 2011():6369-72. PubMed ID: 22255795
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Weighted Transfer Learning for Improving Motor Imagery-Based Brain-Computer Interface.
    Azab AM; Mihaylova L; Ang KK; Arvaneh M
    IEEE Trans Neural Syst Rehabil Eng; 2019 Jul; 27(7):1352-1359. PubMed ID: 31217122
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Preprocessing and meta-classification for brain-computer interfaces.
    Hammon PS; de Sa VR
    IEEE Trans Biomed Eng; 2007 Mar; 54(3):518-25. PubMed ID: 17355065
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Transfer learning with large-scale data in brain-computer interfaces.
    Chun-Shu Wei ; Yuan-Pin Lin ; Yu-Te Wang ; Chin-Teng Lin ; Tzyy-Ping Jung
    Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():4666-4669. PubMed ID: 28269314
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Spectral Transfer Learning Using Information Geometry for a User-Independent Brain-Computer Interface.
    Waytowich NR; Lawhern VJ; Bohannon AW; Ball KR; Lance BJ
    Front Neurosci; 2016; 10():430. PubMed ID: 27713685
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.