[1]杨仁桓,宋爱国,徐宝国.基于谐波小波包变换的脑电波基本节律分析[J].东南大学学报(自然科学版),2008,38(6):996-999.[doi:10.3969/j.issn.1001-0505.2008.06.012]
 Yang Renhuan,Song Aiguo,Xu Baoguo.Analysis of EEG basic rhythms based on discrete harmonic wavelet packet transform[J].Journal of Southeast University (Natural Science Edition),2008,38(6):996-999.[doi:10.3969/j.issn.1001-0505.2008.06.012]
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基于谐波小波包变换的脑电波基本节律分析()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
38
期数:
2008年第6期
页码:
996-999
栏目:
生物医学工程
出版日期:
2008-11-20

文章信息/Info

Title:
Analysis of EEG basic rhythms based on discrete harmonic wavelet packet transform
作者:
杨仁桓 宋爱国 徐宝国
东南大学仪器科学与工程学院, 南京 210096; 东南大学远程测控技术江苏省重点实验室, 南京 210096
Author(s):
Yang Renhuan Song Aiguo Xu Baoguo
School of Instrument Science and Engineering,Southeast University, Nanjing 210096,China
Jiangsu Province Key Laboratory of Remote Measurement and Control, Southeast University, Nanjing 210096,China
关键词:
脑电图 谐波小波包变换 特征提取 癫痫病
Keywords:
electroencephalogram harmonic wavelet packet transform feature extraction epileptic
分类号:
R318.19
DOI:
10.3969/j.issn.1001-0505.2008.06.012
摘要:
为了实现脑电图分析定量化、智能化以便为医学分析诊断提供客观有效的辅助信息,探讨了应用谐波小波包变换分析脑电波.通过谐波小波包变换提取用于临床诊断的δ, θ, α, β等4种基本节律的波形,并引入反映基本节律变化的特征参量即基本节律的频带能量比例进行定量分析. 经过对正常人和癫痫病人的脑电波进行分析验证,其分析结果与先验知识和确诊病症吻合得很好,可以提取得到精确的、量化的、直观的特征参数作为诊断依据.实验结果表明, 应用谐波小波包变换分析脑电波是一种有效的方法,它为脑电图机实现智能化和临床分析诊断提供了有益的参考.
Abstract:
In order to implement intelligent electroencephalogram(EEG)analysis and provide some objective and effective information for medical diagnosis, a new EEG analysis method based on discrete harmonic wavelet packet transform is proposed. First, the four basic rhythms, i.e., δ, θ, α, and β wave, which are very useful for medical diagnosis, are extracted accurately by discrete harmonic wavelet packet transform. Next, based on the transformation, quantitative parameter such as frequency band energy ratio of each basic rhythm from single electrode is introduced to analyze the basic rhythms. The experimental results on healthy person’s EEG and epileptic’s EEG are provided, and the results agree well with prior knowledge and proved diagnosis conclusions. And accurate, quantitative and intuitive feature parameters are obtained. The experimental results demonstrate that the proposed method is an effective way to analyze EEG. It provides a useful reference for intelligent EEG analysis and medical diagnosis.

参考文献/References:

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备注/Memo

备注/Memo:
作者简介: 杨仁桓(1981—),男,博士生; 宋爱国(联系人),男,博士, 教授,博士生导师,a.g.song@seu.edu.cn.
基金项目: 国家高技术研究发展计划(863计划)资助项目(2006AA04Z246)、江苏省国际合作资助项目(BZ2006046)、江苏省普通高校研究生科研创新计划资助项目(CX08B_050Z)、东南大学优秀博士学位论文基金资助项目.
引文格式: 杨仁桓,宋爱国,徐宝国.基于谐波小波包变换的脑电波基本节律分析[
更新日期/Last Update: 2008-11-20