摘要
为有效提取脑电信号特征波,结合小波技术提出一种脑电特征波计算方法。对脑电信号进行小波分解,重构相关频段信号,提取特征波,并结合BP神经网络对其进行计算。实验结果表明,该方法有效,对3个受试者的平均识别率大于80%,适合残疾人等各种人群。
A method which used wavelet package is put forward to extract the feature of Eectroencephalogram（EEG） signals more efficiently. With the help of wavelet, the original EEG signals are decomposed and recomposed at the related frequency range, which is in order to feature extraction, and computed with BP neural network technology. Experimental result shows that the wavelet can extract the feature waves efficiently, which are obtained with more than 80 percent identification rate for three participators, person identification can be used by persons with disabilities and the general public, it has better adaptation.
出处
《计算机工程》
CAS
CSCD
北大核心
2010年第11期27-29,共3页
Computer Engineering
基金
江西省科技厅2008年度青年科学基金资助项目"基于移动平台的脑机接口研究"(2008GQS0003)
江西省教育厅2009年度科技基金资助项目"双人博弈的EEG/ERP与计算机模型研究"(GJJ09622)
关键词
脑电信号
小波
脑电密码
BP神经网络
Eectroencephalogram（EEG） signal
wavelet
EEG password
BP neural network
