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Steady State Visually Evoked Potential Based Brain Computer Interface for Game Control

机译:稳态视觉诱发基于潜在的游戏控制脑电器界面

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This paper presents an electroencephalogram (EEG) based brain computer interface (BCI) design as a control mechanism for the Open Vibe Space shooter game. BCI using Steady State Visual Evoked Potential (SSVEP) is designed. The SSVEP is generated in response to a flickering visual stimulus. The setup uses different flickering frequencies which are displayed on a Liquid Crystal Display (LCD) monitor to elicit SSVEP responses. The EEG signals are recorded over the visual cortex of the brain. These signals are pre-processed to remove undesired information. To extract features, the power information contained in the corresponding frequency bands are calculated. The feature set is fed as an input to the classifier to identify the target class. This study tried to compare the performance of different classification algorithms in terms of accuracy, information transfer rate and the response time. Based on the outcome, support vector machine classifier with radial basis function recorded the best average accuracy of 90%.
机译:本文介绍了基于脑电图(EEG)的脑电脑界面(BCI)设计,作为开放式氛围射击游戏的控制机制。设计了使用稳态视觉诱发电位(SSVEP)的BCI。响应于闪烁的视觉刺激而产生SSVEP。设置使用不同的闪烁频率,这些闪烁频率显示在液晶显示器(LCD)监视器上以引出SSVEP响应。 EEG信号记录在大脑的视觉皮层上。预先处理这些信号以消除不期望的信息。为了提取特征,计算包含在相应频带中的功率信息。要素集被馈送为分类器的输入以标识目标类。本研究试图在准确性,信息传输速率和响应时间方面比较不同分类算法的性能。基于结果,支持向量机分类器具有径向基函数,录制了90%的最佳平均精度。

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