Applying fuzzy theory to the command classification in a steady-state visual evoked potential based brain computer interface

• Main Authors: Wei-ting Liao, 廖偉廷
• Other Authors: Po-Lei Lee
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/92872100598194469311

碩士 === 國立中央大學 === 電機工程研究所 === 98 === The thesis applied Fuzzy Theory to the judgment of steady-state visual evoked potential (SSVEP)-based brain computer interface (BCI).User gazed at flash channels(FCs) that encoded with different phases in order to induce the corresponding SSVEP , so that the gazed FC can be recognized and the command mapping to the gazed FC can be sent out to achieve control purposes. In the thesis, the frequency of FC is 32 Hz, and there are four FCs with different phases 0ﾟ, 90ﾟ, 180ﾟ and 270ﾟ. The SSVEP responses were processed by 20–36 Hz filter and epoch-average.Using Fuzzy Theory to optimize the judgment of BCI system can reduce the occurrence of error judgments. We use a micro-processor to do all the signal process about electroencephalography (EEG), and transmit the result to PC with Bluetooth. PC will sent out the control direction to the robot, and the robot do the actions that user wants.The experiment results show that apply Fuzzy Theory to the judgment of BCI system can increase more 1~12% accuracy than normal judgment theory. Some subjects’ accuracy can even reach 100% by using Fuzzy Theory.