论文标题
基于BCI的智能家庭系统，结合了与事件相关的潜力和语音图像任务
A BCI based Smart Home System Combined with Event-related Potentials and Speech Imagery Task
论文作者
论文摘要
最近，基于脑部计算机界面（BCI）的智能家庭系统在行业和学术界都引起了广泛的兴趣。但是，当前的BCI系统存在几个缺点，因为它在实时实现方面产生了相对较低的精度，并且在这里无法为用户提供直观的范式。因此，在这项研究中，我们提出了一个高度直观的BCI范式，将与事件相关的电位（ERP）与单个目标对象的语音模拟任务结合在一起。所提出的范式的解码精度为88.1％（加上或减去5.90），其性能比常规ERP系统高得多。此外，在语音模拟任务引起的额叶区域，N700组件的幅度显着增强。我们的结果可以用于开发智能家居系统，以便通过直观，准确地传达用户的意图来更加用户友好和方便。
Recently, smart home systems based on brain-computer interface (BCI) has attracted a wide range of interests in both industry and academia. However, the current BCI system has several shortcomings as it produces a comparatively lower accuracy for real-time implementations as well as the intuitive paradigm for the users cannot be well established here. Therefore, in this study, we proposed a highly intuitive BCI paradigm that combines event-related potential (ERP) with the speech-imagery task for the individual target objects. The decoding accuracy of the proposed paradigm was 88.1% (plus or minus 5.90) which is a much significant higher performance than a conventional ERP system. Furthermore, the amplitude of N700 components was significantly enhanced over frontal regions which are priory evoked by the speech-imagery task. Our results could be utilized to develop a smart home system so that it could be more user-friendly and convenient by means of delivering user's intentions both, intuitively and accurately.
