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.
124 related articles for article (PubMed ID: 22255361)
1. Single-trial classification of feedback potentials within neurofeedback training with an EEG brain-computer interface. López-Larraz E; Iterate I; Escolano C; García I; Montesano L; Minguez J Annu Int Conf IEEE Eng Med Biol Soc; 2011; 2011():4596-9. PubMed ID: 22255361 [TBL] [Abstract][Full Text] [Related]
2. EEG single-trial classification of visual, auditive and vibratory feedback potentials in Brain-Computer Interfaces. López-Larraz E; Creatura M; Iturrate I; Montesano L; Minguez J Annu Int Conf IEEE Eng Med Biol Soc; 2011; 2011():4231-4. PubMed ID: 22255273 [TBL] [Abstract][Full Text] [Related]
3. Neurofeedback-based motor imagery training for brain-computer interface (BCI). Hwang HJ; Kwon K; Im CH J Neurosci Methods; 2009 Apr; 179(1):150-6. PubMed ID: 19428521 [TBL] [Abstract][Full Text] [Related]
4. Characteristics of motor imagery based EEG-brain computer interface using combined cue and neuro-feedback. Lee Y; Kim J; Lee S; Lee M Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():4238-41. PubMed ID: 21096902 [TBL] [Abstract][Full Text] [Related]
5. An online EEG-based brain-computer interface for controlling hand grasp using an adaptive probabilistic neural network. Hazrati MKh; Erfanian A Med Eng Phys; 2010 Sep; 32(7):730-9. PubMed ID: 20510641 [TBL] [Abstract][Full Text] [Related]
6. A Comparison between BCI Simulation and Neurofeedback for Forward/Backward Navigation in Virtual Reality. Alchalabi B; Faubert J Comput Intell Neurosci; 2019; 2019():2503431. PubMed ID: 31687005 [TBL] [Abstract][Full Text] [Related]
8. 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]
9. Machine learning for real-time single-trial EEG-analysis: from brain-computer interfacing to mental state monitoring. Müller KR; Tangermann M; Dornhege G; Krauledat M; Curio G; Blankertz B J Neurosci Methods; 2008 Jan; 167(1):82-90. PubMed ID: 18031824 [TBL] [Abstract][Full Text] [Related]
10. Toward unsupervised adaptation of LDA for brain-computer interfaces. Vidaurre C; Kawanabe M; von Bünau P; Blankertz B; Müller KR IEEE Trans Biomed Eng; 2011 Mar; 58(3):587-97. PubMed ID: 21095857 [TBL] [Abstract][Full Text] [Related]
11. The Berlin Brain--Computer Interface: accurate performance from first-session in BCI-naïve subjects. Blankertz B; Losch F; Krauledat M; Dornhege G; Curio G; Müller KR IEEE Trans Biomed Eng; 2008 Oct; 55(10):2452-62. PubMed ID: 18838371 [TBL] [Abstract][Full Text] [Related]
12. Hybrid EEG-EOG brain-computer interface system for practical machine control. Punsawad Y; Wongsawat Y; Parnichkun M Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():1360-3. PubMed ID: 21096331 [TBL] [Abstract][Full Text] [Related]
13. Single-trial EEG source reconstruction for brain-computer interface. Noirhomme Q; Kitney RI; Macq B IEEE Trans Biomed Eng; 2008 May; 55(5):1592-601. PubMed ID: 18440905 [TBL] [Abstract][Full Text] [Related]
14. 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]
15. Motor imagery and action observation: modulation of sensorimotor brain rhythms during mental control of a brain-computer interface. Neuper C; Scherer R; Wriessnegger S; Pfurtscheller G Clin Neurophysiol; 2009 Feb; 120(2):239-47. PubMed ID: 19121977 [TBL] [Abstract][Full Text] [Related]
16. EEG auditory steady state responses classification for the novel BCI. Higashi H; Rutkowski TM; Washizawa Y; Cichocki A; Tanaka T Annu Int Conf IEEE Eng Med Biol Soc; 2011; 2011():4576-9. PubMed ID: 22255356 [TBL] [Abstract][Full Text] [Related]
17. Real-time EEG feedback during simultaneous EEG-fMRI identifies the cortical signature of motor imagery. Zich C; Debener S; Kranczioch C; Bleichner MG; Gutberlet I; De Vos M Neuroimage; 2015 Jul; 114():438-47. PubMed ID: 25887263 [TBL] [Abstract][Full Text] [Related]
18. 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; 14(2):225-9. PubMed ID: 16792300 [TBL] [Abstract][Full Text] [Related]
19. The Impact of Different Visual Feedbacks in User Training on Motor Imagery Control in BCI. Zapała D; Francuz P; Zapała E; Kopiś N; Wierzgała P; Augustynowicz P; Majkowski A; Kołodziej M Appl Psychophysiol Biofeedback; 2018 Mar; 43(1):23-35. PubMed ID: 29075937 [TBL] [Abstract][Full Text] [Related]
20. Masked and unmasked error-related potentials during continuous control and feedback. Lopes Dias C; Sburlea AI; Müller-Putz GR J Neural Eng; 2018 Jun; 15(3):036031. PubMed ID: 29557346 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]