Perakakis Pandelis, Taylor Michael, Martinez-Nieto Eduardo, Revithi Ioanna, Vila Jaime
Department of Personality, University of Granada, Spain.
Biol Psychol. 2009 Sep;82(1):82-8. doi: 10.1016/j.biopsycho.2009.06.004. Epub 2009 Jun 25.
Detrended Fluctuation Analysis (DFA) is an algorithm widely used to determine fractal long-range correlations in physiological signals. Its application to heart rate variability (HRV) has proven useful in distinguishing healthy subjects from patients with cardiovascular disease. In this study we examined the effect of respiratory sinus arrhythmia (RSA) on the performance of DFA applied to HRV. Predictions based on a mathematical model were compared with those obtained from a sample of 14 normal subjects at three breathing frequencies: 0.1Hz, 0.2Hz and 0.25Hz. Results revealed that: (1) the periodical properties of RSA produce a change of the correlation exponent in HRV at a scale corresponding to the respiratory period, (2) the short-term DFA exponent is significantly reduced when breathing frequency rises from 0.1Hz to 0.2Hz. These findings raise important methodological questions regarding the application of fractal measures to short-term HRV.
去趋势波动分析（DFA）是一种广泛用于确定生理信号中分形长程相关性的算法。它在心率变异性（HRV）中的应用已被证明有助于区分健康受试者和心血管疾病患者。在本研究中，我们研究了呼吸性窦性心律不齐（RSA）对应用于HRV的DFA性能的影响。将基于数学模型的预测与从14名正常受试者样本在三种呼吸频率（0.1Hz、0.2Hz和0.25Hz）下获得的预测进行了比较。结果显示：（1）RSA的周期性特性在与呼吸周期相对应的尺度上导致HRV中相关指数的变化，（2）当呼吸频率从0.1Hz升至0.2Hz时，短期DFA指数显著降低。这些发现提出了关于将分形测量应用于短期HRV的重要方法学问题。
