764 related articles for article (PubMed ID: 22498703)
1. 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; 20(3):379-88. PubMed ID: 22498703
[TBL] [Abstract][Full Text] [Related]
2. 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; 6(4):046005. PubMed ID: 19556679
[TBL] [Abstract][Full Text] [Related]
3. A comparison of three brain-computer interfaces based on event-related desynchronization, steady state visual evoked potentials, or a hybrid approach using both signals.
Brunner C; Allison BZ; Altstätter C; Neuper C
J Neural Eng; 2011 Apr; 8(2):025010. PubMed ID: 21436538
[TBL] [Abstract][Full Text] [Related]
4. A motor imagery-based online interactive brain-controlled switch: paradigm development and preliminary test.
Qian K; Nikolov P; Huang D; Fei DY; Chen X; Bai O
Clin Neurophysiol; 2010 Aug; 121(8):1304-13. PubMed ID: 20347386
[TBL] [Abstract][Full Text] [Related]
5. Evaluation and application of a hybrid brain computer interface for real wheelchair parallel control with multi-degree of freedom.
Li J; Ji H; Cao L; Zang D; Gu R; Xia B; Wu Q
Int J Neural Syst; 2014 Jun; 24(4):1450014. PubMed ID: 24694169
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. 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; 5(1):24-35. PubMed ID: 18310808
[TBL] [Abstract][Full Text] [Related]
8. A brain-computer interface driven by imagining different force loads on a single hand: an online feasibility study.
Wang K; Wang Z; Guo Y; He F; Qi H; Xu M; Ming D
J Neuroeng Rehabil; 2017 Sep; 14(1):93. PubMed ID: 28893295
[TBL] [Abstract][Full Text] [Related]
9. 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
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. 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]
12. How many people are able to control a P300-based brain-computer interface (BCI)?
Guger C; Daban S; Sellers E; Holzner C; Krausz G; Carabalona R; Gramatica F; Edlinger G
Neurosci Lett; 2009 Oct; 462(1):94-8. PubMed ID: 19545601
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. A hybrid brain computer interface to control the direction and speed of a simulated or real wheelchair.
Long J; Li Y; Wang H; Yu T; Pan J; Li F
IEEE Trans Neural Syst Rehabil Eng; 2012 Sep; 20(5):720-9. PubMed ID: 22692936
[TBL] [Abstract][Full Text] [Related]
15. Self-paced operation of an SSVEP-Based orthosis with and without an imagery-based "brain switch:" a feasibility study towards a hybrid BCI.
Pfurtscheller G; Solis-Escalante T; Ortner R; Linortner P; Müller-Putz GR
IEEE Trans Neural Syst Rehabil Eng; 2010 Aug; 18(4):409-14. PubMed ID: 20144923
[TBL] [Abstract][Full Text] [Related]
16. 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; 10(2):026009. PubMed ID: 23428907
[TBL] [Abstract][Full Text] [Related]
17. 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
[TBL] [Abstract][Full Text] [Related]
18. EEG-based classification of imaginary left and right foot movements using beta rebound.
Hashimoto Y; Ushiba J
Clin Neurophysiol; 2013 Nov; 124(11):2153-60. PubMed ID: 23757379
[TBL] [Abstract][Full Text] [Related]
19. The impact of loss of control on movement BCIs.
Reuderink B; Poel M; Nijholt A
IEEE Trans Neural Syst Rehabil Eng; 2011 Dec; 19(6):628-37. PubMed ID: 21984517
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
