Asynchronous BCI control using high-frequency SSVEP.

Asynchronous BCI control using high-frequency SSVEP.
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DOI:
10.1186/1743-0003-8-39
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发表时间:
2011-07-14
影响因子:
5.1
通讯作者:
Laciar Leber E
Laciar Leber E
中科院分区:
工程技术2区
文献类型:
--
作者:
Diez PF;Mut VA;Avila Perona EM;Laciar Leber E

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稳态视觉诱发电位(Steady-State Visual Evoked Potential,SSVEP)是一种由频率高于4 Hz的光源反复刺激诱发的视觉皮层反应,可分为低频(12 Hz以下)、中频(12-30 Hz)和高频(> 30 Hz)三个范围。基于SSVEP的脑机接口(BCI)主要集中在低频和中频范围内,而高频范围内只有少数项目。然而,他们只评估不同方法提取SSVEP的性能。本研究提出一种基于高频SSVEP的异步脑机接口,以控制屏幕上的移动的物体通过场景导航并到达其最终目的地。这可以帮助残疾人驾驶机器人轮椅。有三个不同的场景,不同的难度等级(容易,中等和困难)。信号处理方法是基于傅立叶变换和三个EEG测量通道。该研究获得的精度范围从65%到100%的分类与信息传输速率从9.4到45位/分钟。我们提出的方法允许所有参与研究的受试者控制的移动的对象,并达到最终的目标,而无需事先培训。
Steady-State Visual Evoked Potential (SSVEP) is a visual cortical response evoked by repetitive stimuli with a light source flickering at frequencies above 4 Hz and could be classified into three ranges: low (up to 12 Hz), medium (12-30) and high frequency (> 30 Hz). SSVEP-based Brain-Computer Interfaces (BCI) are principally focused on the low and medium range of frequencies whereas there are only a few projects in the high-frequency range. However, they only evaluate the performance of different methods to extract SSVEP. This research proposed a high-frequency SSVEP-based asynchronous BCI in order to control the navigation of a mobile object on the screen through a scenario and to reach its final destination. This could help impaired people to navigate a robotic wheelchair. There were three different scenarios with different difficulty levels (easy, medium and difficult). The signal processing method is based on Fourier transform and three EEG measurement channels. The research obtained accuracies ranging in classification from 65% to 100% with Information Transfer Rate varying from 9.4 to 45 bits/min. Our proposed method allows all subjects participating in the study to control the mobile object and to reach a final target without prior training.
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