三种非线性趋势项的提取方法在生物医学信号分析中的应用

Application of Three Kinds of Method for Extracting Nonlinear Trend in Biomedical Signal Analysis

在生物医学信号的分析中往往需要将信号中的趋势成分和非趋势成分进行分离来实现不同的信号分析及应用的目的。该文介绍了三种应用在生物医学信号处理中的用于分离非平稳信号中的非线性趋势的分析方法:小波分析法,经验模式分析法和平滑先验法的原理,并应用它们对三种实际的生物医学信号的数据进行趋势信号与非趋势信号分离的应用举例。提示在非线性的趋势分析中,可根据不同的分析目的和不同的信号特征来选择不同的方法进行应用。

Biomedical signal analysis often needs to separate the trend component from the non-trend component to achieve different purposes and applications in signal analysis. This article introduces three kinds of detrending nonlinear component methods used in the process of biomedical signal analysis： wavelet analysis, empirical mode decomposition. smoothness priors approach as wel as the application in the separation of the actual biomedical data. The different separation methods should be selected according to different research goals as wel as the feature of the signal.