一种基于FPGA的脑电分类算法实现  

EEG sorting algorithm based on FPGA

作　　者：刘纪红[1] 丁俊杰[1] 边洪亮[1] 

机构地区：[1]东北大学信息科学与工程学院,辽宁沈阳110819

出　　处：《现代电子技术》2012年第20期107-110,共4页Modern Electronics Technique

基　　金：国家自然科学基金资助项目(60774097)

摘　　要：通过对脑电信号特征的分析,利用小波变换的多尺度分析技术对脑电信号进行特征提取,进而使用主成分分析算法对特征进行降维,并对降维后的信号使用Fisher线性判别方法进行分类。最后,利用VerilogHDL硬件编程语言设计实现了Mallat分解算法、PCA算法和LDA算法模块,并在FPGA应用板上实现了脑电分类功能。系统对2008年BCI大赛的数据进行了测试,分类准确率达到92.31%,表明该方法对开发便携式脑机接口系统具有良好的应用价值。After analysis of the EEG signal characteristics,the EEG signal feature was extracted with multiresolution analysis technology of wavelet transform.The principal component analysis（PCA） algorithm is applied for dimensionality reduction of the features.Then,the signals after dimensionality reduction is sorted with Fisher linear discriminatory analysis（LDA） algorithm.Finally,the algorithm modules of Mallat decomposition,PCA and LDA are designed by using the hardware programming language Verilog HDL,and the function of the EEG recognition system is realized on the FPGA application board.The data obtained from the 2008 BCI contest was tested by the system.The classification accuracy reached 92.31%.The results show that this method has good application value in developping portable brain-computer interface system.

关 键 词：脑机接口 小波变换 主成分分析 线性判别分析 

分 类 号：TN911-34[电子电信—通信与信息系统] TP315[电子电信—信息与通信工程]