Department of Physiological Sciences, Federal University of Espírito Santo, Av. Marechal Campos, Vitoria, Espírito Santo, Brazil.
Comput Biol Med. 2012 Feb;42(2):164-70. doi: 10.1016/j.compbiomed.2011.11.004. Epub 2011 Dec 2.
This work assessed the influence of the autoregressive model order (ARMO) on the spectral analysis of the heart rate variability (HRV). A sample of 68 R-R series obtained from digital ECG records of young healthy adults in the supine position was used. Normalized spectral indexes for each ARMO were compared by Friedman test followed by the Dunn's procedure and statistical significance was set at P<0.05. The results showed that the AR method using orders from 9 to 25 produces normalized spectral parameters statistically similar and, hence, the algorithms commonly employed to estimate optimum order are not mandatory in this case.
这项工作评估了自回归模型阶数 (ARMO) 对心率变异性 (HRV) 谱分析的影响。使用了仰卧位的年轻健康成年人数字心电图记录中获得的 68 个 R-R 系列样本。通过 Friedman 检验后进行 Dunn 程序比较每个 ARMO 的归一化谱指数,统计显著性设置为 P<0.05。结果表明,使用 9 到 25 阶的 AR 方法产生的归一化谱参数在统计学上是相似的,因此,在这种情况下,通常用于估计最佳阶数的算法并非强制性的。