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Items: 1 to 20 of 243

1.

Prediction of SSVEP-based BCI performance by the resting-state EEG network.

Zhang Y, Xu P, Guo D, Yao D.

J Neural Eng. 2013 Dec;10(6):066017. doi: 10.1088/1741-2560/10/6/066017. Epub 2013 Nov 27.

PMID:
24280591
2.

SSVEP response is related to functional brain network topology entrained by the flickering stimulus.

Zhang Y, Xu P, Huang Y, Cheng K, Yao D.

PLoS One. 2013 Sep 9;8(9):e72654. doi: 10.1371/journal.pone.0072654. eCollection 2013.

3.

An amplitude-modulated visual stimulation for reducing eye fatigue in SSVEP-based brain-computer interfaces.

Chang MH, Baek HJ, Lee SM, Park KS.

Clin Neurophysiol. 2014 Jul;125(7):1380-91. doi: 10.1016/j.clinph.2013.11.016. Epub 2013 Dec 1.

PMID:
24368034
4.

Assisted closed-loop optimization of SSVEP-BCI efficiency.

Fernandez-Vargas J, Pfaff HU, Rodríguez FB, Varona P.

Front Neural Circuits. 2013 Feb 25;7:27. doi: 10.3389/fncir.2013.00027. eCollection 2013.

5.

Classification of binary intentions for individuals with impaired oculomotor function: 'eyes-closed' SSVEP-based brain-computer interface (BCI).

Lim JH, Hwang HJ, Han CH, Jung KY, Im CH.

J Neural Eng. 2013 Apr;10(2):026021. doi: 10.1088/1741-2560/10/2/026021. Epub 2013 Mar 26. Erratum in: J Neural Eng. 2013 Jun;10(3):049501.

PMID:
23528484
6.

On the quantification of SSVEP frequency responses in human EEG in realistic BCI conditions.

Kuś R, Duszyk A, Milanowski P, Łabęcki M, Bierzyńska M, Radzikowska Z, Michalska M, Zygierewicz J, Suffczyński P, Durka PJ.

PLoS One. 2013 Oct 18;8(10):e77536. doi: 10.1371/journal.pone.0077536. eCollection 2013.

7.

Brain-computer interfaces using capacitive measurement of visual or auditory steady-state responses.

Baek HJ, Kim HS, Heo J, Lim YG, Park KS.

J Neural Eng. 2013 Apr;10(2):024001. doi: 10.1088/1741-2560/10/2/024001. Epub 2013 Feb 28.

PMID:
23448913
8.

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. doi: 10.1088/1741-2560/8/2/025010. Epub 2011 Mar 24.

PMID:
21436538
9.

Brain-computer interface based on intermodulation frequency.

Chen X, Chen Z, Gao S, Gao X.

J Neural Eng. 2013 Dec;10(6):066009. doi: 10.1088/1741-2560/10/6/066009. Epub 2013 Oct 18.

PMID:
24140740
10.

A new dual-frequency stimulation method to increase the number of visual stimuli for multi-class SSVEP-based brain-computer interface (BCI).

Hwang HJ, Hwan Kim D, Han CH, Im CH.

Brain Res. 2013 Jun 17;1515:66-77. doi: 10.1016/j.brainres.2013.03.050. Epub 2013 Apr 13.

PMID:
23587933
11.

A hybrid BCI speller paradigm combining P300 potential and the SSVEP blocking feature.

Xu M, Qi H, Wan B, Yin T, Liu Z, Ming D.

J Neural Eng. 2013 Apr;10(2):026001. doi: 10.1088/1741-2560/10/2/026001. Epub 2013 Jan 31.

PMID:
23369924
12.

An Idle-State Detection Algorithm for SSVEP-Based Brain-Computer Interfaces Using a Maximum Evoked Response Spatial Filter.

Zhang D, Huang B, Wu W, Li S.

Int J Neural Syst. 2015 Nov;25(7):1550030. doi: 10.1142/S0129065715500306. Epub 2015 Jul 5.

PMID:
26246229
13.

Frequency recognition methods for dual-frequency SSVEP based brain-computer interface.

Chang MH, Park KS.

Conf Proc IEEE Eng Med Biol Soc. 2013;2013:2220-3. doi: 10.1109/EMBC.2013.6609977.

PMID:
24110164
14.

Sequence detection analysis based on canonical correlation for steady-state visual evoked potential brain computer interfaces.

Cao L, Ju Z, Li J, Jian R, Jiang C.

J Neurosci Methods. 2015 Sep 30;253:10-7. doi: 10.1016/j.jneumeth.2015.05.014. Epub 2015 May 23.

PMID:
26014663
15.

Frequency-modulated steady-state visual evoked potentials: a new stimulation method for brain-computer interfaces.

Dreyer AM, Herrmann CS.

J Neurosci Methods. 2015 Feb 15;241:1-9. doi: 10.1016/j.jneumeth.2014.12.004. Epub 2014 Dec 15.

PMID:
25522824
16.

A novel stimulation for multi-class SSVEP-based brain-computer interface using patterns of time-varying frequencies.

Dehzangi O, Nathan V, Zong C, Lee C, Kim I, Jafari R.

Conf Proc IEEE Eng Med Biol Soc. 2014;2014:118-21. doi: 10.1109/EMBC.2014.6943543.

PMID:
25569911
17.

Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain-computer interface.

Chen X, Wang Y, Gao S, Jung TP, Gao X.

J Neural Eng. 2015 Aug;12(4):046008. doi: 10.1088/1741-2560/12/4/046008. Epub 2015 Jun 2.

PMID:
26035476
18.

Customized stimulation enhances performance of independent binary SSVEP-BCIs.

Lopez-Gordo MA, Prieto A, Pelayo F, Morillas C.

Clin Neurophysiol. 2011 Jan;122(1):128-33. doi: 10.1016/j.clinph.2010.05.021. Epub 2010 Jun 22.

PMID:
20573542
19.

Multivariate synchronization index for frequency recognition of SSVEP-based brain-computer interface.

Zhang Y, Xu P, Cheng K, Yao D.

J Neurosci Methods. 2014 Jan 15;221:32-40. doi: 10.1016/j.jneumeth.2013.07.018. Epub 2013 Aug 6.

PMID:
23928153
20.

SSVEP recognition using common feature analysis in brain-computer interface.

Zhang Y, Zhou G, Jin J, Wang X, Cichocki A.

J Neurosci Methods. 2015 Apr 15;244:8-15. doi: 10.1016/j.jneumeth.2014.03.012. Epub 2014 Apr 13.

PMID:
24727656
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