Spectral analysis of bioelectric signals by adapted wavelet transforms

U. Wiklund, M. Akay
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引用次数: 1

Abstract

In this study we use the adapted wavelet transform methods (wavelet and cosine packets) for spectral analysis of bioelectric signals. These methods have recently been introduced for analysis of non-stationary signals. Using recordings of the heart rate variability in twenty healthy subjects, the estimated power in different frequency bands is compared to results based on the classical methods: fast Fourier transform and autoregressive modelling. The results showed that cosine packets gave similar results to classical methods, and may be preferred to characterise the rhythmic components in the recorded signals. On the other hand, the non-stationary fluctuations, i.e., the "trend", was efficiently decomposed using the wavelet transform method.
基于自适应小波变换的生物电信号频谱分析
在本研究中,我们使用自适应的小波变换方法(小波和余弦包)进行生物电信号的频谱分析。这些方法最近被引入非平稳信号的分析。利用20名健康受试者的心率变异性记录,将不同频段的估计功率与基于快速傅立叶变换和自回归建模的经典方法的结果进行了比较。结果表明,余弦包给出了与经典方法相似的结果,可能更适合于表征记录信号中的节奏成分。另一方面,利用小波变换方法对非平稳波动即“趋势”进行了有效分解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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