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Wavelet decomposition analysis of heart rate variability in aerobic athletes.

机译:有氧运动员心率变异性的小波分解分析。

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Heart rate variability (HRV) can be quantified, among others, in the frequency domain using digital signal processing (DSP) techniques. The wavelet transform is an alternative tool for the analysis of non-stationary signals. The implementation of perfect reconstruction digital filter banks leads to multi resolution wavelet analysis. Software was developed in LabVIEW. In this study, the average power was compared at each decomposition level of a tachogram, containing the consecutive RR-intervals of two groups of subjects: aerobic athletes and a control group. Compared to the controls, the aerobic athletes showed an increased power in all frequency bands. These results are in accordance with values obtained by spectral analysis using the Fourier transform, suggesting that wavelet analysis could be an appropriate tool to evaluate oscillating components in HRV, but in addition to classic methods, it also gives a time resolution.
机译:可以使用数字信号处理(DSP)技术在频域中量化心率变异性(HRV)。小波变换是用于分析非平稳信号的替代工具。完美重构数字滤波器组的实施导致多分辨率小波分析。该软件是在LabVIEW中开发的。在这项研究中,比较了转速记录图每个分解级别的平均功率,其中包含两组对象(有氧运动者和对照组)的连续RR间隔。与对照组相比,有氧运动员在所有频段上的力量都增加了。这些结果与使用傅立叶变换通过频谱分析获得的值一致,表明小波分析可能是评估HRV中振荡分量的合适工具,但除了经典方法外,它还提供了时间分辨率。

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