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Spectral analysis of bioelectric signals by adapted wavelet transforms

机译:通过调整小波变换的生物电信号光谱分析

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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.
机译:在该研究中,我们使用适应的小波变换方法(小波和余弦分组)来进行生物电信号的光谱分析。最近介绍了这些方法以分析非静止信号。使用20个健康受试者的心率变异性的录制,将不同频带的估计功率与基于经典方法的结果进行比较:快速傅里叶变换和自回归建模。结果表明,余弦分组对典型方法具有类似的结果,并且可以优选地表征记录信号中的节奏分量。另一方面,使用小波变换方法有效地分解非静止波动,即“趋势”。

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