The application of wavelet packets to the analysis of dynamic electroencephalogram

Shen Minfen, Zheng Yi
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引用次数: 2

Abstract

In this paper we propose a new method for dynamic analysis of EEG signals. Multiresolution decomposition is used to investigate the transition of clinical EEG signals. Wavelet packet transformation is investigated for designing filters with different frequency characteristics in order to detect different kinds of EEG rhythms. Real EEG signals with different brain function states are tested and analyzed. It is shown from the experimental results that the dynamic characteristics of clinical brain electrical activities can be demonstrated by using the wavelet transformation. The method presented in this paper also proposes a new way for the analysis of other biomedical signals.
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小波包在动态脑电图分析中的应用
本文提出了一种新的脑电信号动态分析方法。采用多分辨率分解方法研究临床脑电信号的转换。研究了用小波包变换设计不同频率特征的滤波器,以检测不同类型的脑电节律。对不同脑功能状态下的真实脑电信号进行了测试和分析。实验结果表明,应用小波变换可以表征临床脑电活动的动态特征。本文提出的方法也为其他生物医学信号的分析提供了一种新的方法。
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