%0 Journal Article
%T Automatic detection of epileptiform wave in EEG by multi-resolution analysis<br>基于多分辨分析的脑电癫痫波自动检测*
%A WANG Chun-mei
%A ZOU Jun-zhong
%A ZHANG Jian
%A ZHANG Zhi-suo
%A <br>汪春梅
%A 邹俊忠
%A 张见
%A 张志锁
%J 计算机应用研究
%D 2009
%I 
%X This paper proposed a new scheme for detecting epileptiform activity in 8-channel EEG based on the characteristic of a multi-resolution analysis. The EEG signal on each channel was decomposed to five levels using discrete wavelet transform. Formed wavelet coefficients and standard deviation of all 8-channel raw data to compute adaptive threshold, which applied on sub-bands1, 2 and 3. Then extracted the spike portion of EEG signal extracted from the raw data. The key points of this research work were identification of a suitable wavelet for decomposition of EEG signals, recognition of a proper resolution level, and computation of a dynamic threshold. The experiment results show that the proposed method offers a fast and effective measure for detecting epileptiform activity in human EEG.
%K electroencephalogram(EEG)
%K epileptiform activity
%K multi-resolution analysis
%K automatic detection<br>脑电信号
%K 癫痫波
%K 多分辨分析
%K 自动检测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=ACED0CC89ADF4F367752EC0C4E99CC89&yid=DE12191FBD62783C&vid=96C778EE049EE47D&iid=5D311CA918CA9A03&sid=8235FE4E203F2DE2&eid=5AD22DF6AAE82463&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=8