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Brain Journal-Novel Detection Features For Ssvep Based Bci: Coefficient Of Variation And Variation Speed-Figure 4: Visual Stimuli

appsOther research productkeyboard_double_arrow_right Image 27 Jul 2017 English Publisher:Zenodo
Authors: Can Bülent Fidan; Abdullah Talha Sözer;

doi: 10.5281/zenodo.1189402 , 10.5281/zenodo.1189403

Brain Journal-Novel Detection Features For Ssvep Based Bci: Coefficient Of Variation And Variation Speed-Figure 4: Visual Stimuli

Abstract

In order to test the developed features, the SSVEP datasets recorded in (Nakanishi et al. 2014) is used. Flickering boxes had been presented on 24-inch LCD monitor with a refresh rate of 75Hz. 32 visual stimuli had been generated with 8 different frequencies (8 Hz, 9 Hz, …, 15 Hz) and 4 different phases (0o , 90o , 180o , 270o ) as shown in Figure 4. Thirteen healthy adults had participated in the experiments. EEG data had been recorded by 16 electrodes (FPz, F3, F4, Fz, Cz, P1, P2, Pz, PO3, PO4, PO7, PO8, POz, O1, O2 and Oz). The sampling rate had been 512 Hz. The datasets are grouped into 4 groups. The 0-degree stimuli formed the 1st group, the 90- degree stimuli the 2nd group, the 180-degree stimuli the 3rd group and the 270-degree stimuli the 4th group. Thus, it is made possible to test the developed features in more datasets.

https://www.edusoft.ro/brain/index.php/brain/article/view/694/782

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Keywords

detection feature, Steady-state visual evoked potential, Brain computer interface

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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