Kuss Oliver, Schumann Barbara, Kluttig Alexander, Greiser Karin Halina, Haerting Johannes
Institute of Medical Epidemiology, Biostatistics, and Informatics, Medical Faculty, University of Halle-Wittenberg, Halle, Saale, Germany.
J Electrocardiol. 2008 Jul-Aug;41(4):287-91. doi: 10.1016/j.jelectrocard.2008.02.014. Epub 2008 Mar 25.
Measures of heart rate variability (HRV) can be divided in time domain and frequency domain parameters. It is frequently ignored that estimation of frequency-domain parameters is a 2-step procedure where statistical error from the first step (spectral estimation) is neglected in subsequent analyses.
We performed a simulation study to quantify the statistical error by using frequency domain instead of time domain parameters. We generated tachograms from a stationary AR(1) process for a wide range of parameters and compared the resulting estimation error (in terms of precision and variability) for the standard deviation of normal RR intervals (SDNN) and low frequency (LF), high frequency (HF), and LF/HF power.
Estimation of frequency domain parameters is associated with (up to 10-fold) increased variability, as compared with the SDNN. Moreover, the SDNN has higher precision.
Frequency domain parameters should be applied in HRV analysis only if important physiological reasons suggest their use. If used, frequency domain parameters should be interpreted with caution, taking into account the statistical weaknesses of spectral estimation.
心率变异性（HRV）测量可分为时域和频域参数。经常被忽视的是，频域参数估计是一个两步过程，在后续分析中忽略了第一步（频谱估计）的统计误差。
我们进行了一项模拟研究，通过使用频域而非时域参数来量化统计误差。我们针对广泛的参数范围，从平稳自回归（AR(1)）过程生成心动周期图，并比较了正常RR间期标准差（SDNN）以及低频（LF）、高频（HF）和LF/HF功率估计误差（在精度和变异性方面）。
与SDNN相比，频域参数估计的变异性增加（高达10倍）。此外，SDNN具有更高的精度。
仅当重要的生理原因表明应使用频域参数时，才应将其应用于HRV分析。如果使用，考虑到频谱估计的统计弱点，频域参数的解释应谨慎。
