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诱发电位中自发脑电的白化及去除
引用本文:官金安,陈亚光.诱发电位中自发脑电的白化及去除[J].数理医药学杂志,2006,19(4):412-414.
作者姓名:官金安  陈亚光
作者单位:中南民族大学电子信息工程学院,武汉,430074
基金项目:国家自然科学基金;中南民族大学校科研和校改项目
摘    要:从被淹没在数十微伏的自发脑电背景中单次提取微伏级的视觉诱发电位,是脑-计算机接口的核心问题之一。将靶刺激出现前记录到的短时非靶刺激信号看作自发脑电,计算自回归模型参数,构造一个白化滤波器,再将实时信号通过上述白化滤波器进行滤波,使自发脑电得以白化,然后采用普通数字滤波器滤除白躁信号,使得非靶信号幅值更小,靶刺激信号更加突出。与不用白化滤波器进行对比实验相比,模式分类的正确率得到了提高。

关 键 词:自回归模型  白化滤波器  小波  诱发电位
文章编号:1004-4337(2006)04-0412-03
修稿时间:2006年1月10日

Eliminating Spontaneous EEG from Evoked Potentials Via Whiten Filter and Wavelet Threshold Denoising
Guan Jinan,et al.Eliminating Spontaneous EEG from Evoked Potentials Via Whiten Filter and Wavelet Threshold Denoising[J].Journal of Mathematical Medicine,2006,19(4):412-414.
Authors:Guan Jinan  
Abstract:One of the key issues in a brain computer interface is to single-trial estimate the visual evoked potentials which embedded in ongoing spontaneous Electroencephalogram(EEG) background.As the spontaneous EEG could be regarded as a stationary random process in a short period,a whiten filter was constructed by the AR parameters which calculated from those non-target signals.In succession,real-world signals were input to the filter where the spontaneous EEGs were whitened.Finally,a lowpass filter was applied to have the white signals filtered.The comparative research shows that the classification accuracy is improved by suppressing the non-target signals and enhancing the target signals.
Keywords:AR model  whiten filter  brain-computer interface  electroencephalogram
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