Evaluation of the preference by the EEG

在本课题中，我们构建了超紧凑的脑电图测量仪，并提出了感官评价方法。第一年，我们构建了脑电测量仪。在脑电图中，有很多噪声。这是一个严重的问题。然后提出了基于Simple-FLDA的脑电信号与噪声分离方法。进一步得出脑电测点的重要性。通过使用超紧凑的脑电图系统，我们可以得到食欲（或欲望），例如他/她想上厕所。他们想吃点东西。然而，在今年，我们不能决定哪些乐队对他们的胃口很重要。在接下来的一年里，我们可以得到频率的组合（即14Hz和21Hz对听音乐很重要）。这些组合是通过使用遗传算法得到的。通过研究结果，我们可以看出频率组合对未来轮椅EEG控制器项目的重要性。

In this project, we construct the super-compact EEG measurement instrument and proposed the sensory evaluation method. The first year, we construct the EEG measurement instrument. In the EEG, there are a lot of noises. It is the serious problem. Then we proposed the separation method for EEG and noises by using the Simple-FLDA. Furthermore, we can get the importance of EEG measurement points. By using the super compact EEG system, we can get the appetite (or desire), e.g. He/ She want to go toilet. They want to something to eat. However in this year we can not decide which bands are important for their appetite. In the next year, we can obtain the combination of the frequency (i.e., 14Hz and 21Hz are important for the listening to music.) These combinations are found out by using the GA. By the results, we can figure on the importance of the combination the frequencies for the future project as an EEG controller for wheelchair.