2015 34th Chinese Control Conference (CCC) 2015
DOI: 10.1109/chicc.2015.7260370
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Design of an online BCI system based on CCA detection method

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Cited by 4 publications
(2 citation statements)
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“…As regards the obtained accuracies in absolute terms, our results are in line with literature regarding multiclass SSVEP recognition with the standard CCA technique [ 7 , 14 , 20 , 26 , 32 ], although a subject-specific calibration of the stimulation frequencies and/or their duty cycles [ 33 ] could have further increased the performances. In addition, we verified that the combination of our proposed variations could produce the same accuracy increments as other CCA-related methods in literature and particularly the same improvements as filter bank CCA of Chen et al [ 26 ].…”
Section: Discussionsupporting
confidence: 88%
“…As regards the obtained accuracies in absolute terms, our results are in line with literature regarding multiclass SSVEP recognition with the standard CCA technique [ 7 , 14 , 20 , 26 , 32 ], although a subject-specific calibration of the stimulation frequencies and/or their duty cycles [ 33 ] could have further increased the performances. In addition, we verified that the combination of our proposed variations could produce the same accuracy increments as other CCA-related methods in literature and particularly the same improvements as filter bank CCA of Chen et al [ 26 ].…”
Section: Discussionsupporting
confidence: 88%
“…Though the efficiency of such a system is very good, user training is mandatory which may not be desirable in some cases. In another system, an online BCI system has been designed using the steady state visually evoked potential [6] to control the robotic arm [10]. The main drawback of this system is that a computer and the related software needs to be setup.…”
Section: Introductionmentioning
confidence: 99%