Errors in the Estimation of Approximate Entropy and Other Recurrence-Plot-Derived Indices Due to the Finite Resolution of RR Time Series
Errors in the Estimation of Approximate Entropy and Other Recurrence-Plot-Derived Indices Due to the Finite Resolution of RR Time Series
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DOI：
10.1109/tbme.2008.2005951
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发表时间：
2009-02-01
影响因子：
4.6
通讯作者：
Ramos-Castro, Juan
中科院分区：
文献类型：
--
作者：
Garcia-Gonzalez, Miguel A.;Fernandez-Chimeno, Mireya;Ramos-Castro, Juan
分析了由于RR时间序列的有限分辨率在近似熵（ApEn）估计中的误差。当信号变异性或采样频率较低时，离散RR时间序列中的量化误差会在近似熵估计中产生相当大的误差（偏差和方差）。类似的错误可以发现在有关的量化复发曲线的指数。提出了一种计算品质因数[信号与邻域分辨率比（SRN）]的简单方法，以便预测索引中的偏差何时可能较高。当SRN接近整数值n时，偏置高于接近n - 1/2或n + 1/2时的偏置。此外，如果SRN接近整数值，则该值越低，偏差越大。
An analysis of the errors due to the finite resolution of RR time series in the estimation of the approximate entropy (ApEn) is described. The quantification errors in the discrete RR time series produce considerable errors in the ApEn estimation (bias and variance) when the signal variability or the sampling frequency is low. Similar errors can be found in indices related to the quantification of recurrence plots. An easy way to calculate a figure of merit [the signal to resolution of the neighborhood ratio (SRN)] is proposed in order to predict when the bias in the indices could be high. When SRN is close to an integer value n, the bias is higher than when near n - 1/2 or n + 1/2. Moreover, if SRN is close to an integer value, the lower this value, the greater the bias is.