首页> 外文期刊>Korean Circulation Journal >A Low Frequency Oscillation in Pulmonary Circulation and Its Dynamic Relation to the Low Frequency Oscillation of Systemic Circulation : Power Spectrum and Phase Estimation by Autoregressive Algorithm and Cross Spectral Analysis
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A Low Frequency Oscillation in Pulmonary Circulation and Its Dynamic Relation to the Low Frequency Oscillation of Systemic Circulation : Power Spectrum and Phase Estimation by Autoregressive Algorithm and Cross Spectral Analysis

机译:肺循环中的低频振荡及其与系统循环中的低频振荡的动态关系:功率谱和相位估计的自回归算法和互谱分析

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Background Low frequency oscillation of systemic artery pressure was known as the marker of sympathetic modulation. Recently the low frequency oscillation of pulmonay artery pressure in pulmonary hypertensive patient was reported. But no further study about its quantitative relationshop and phasic coupling between the low frequency oscillation of pulmonary artery pressure and systemic artery pressure. Power spectral analysis with autoregressive algorithm and cross spectral analysis are powerful tool for investigation these relationship. Method Analog signals of simultaneous measured left pulmonary and femoral artery pressure in thirty one patients with ventricular septal defect were digitized and stored. After modeling each time series with autoregressive algorithm, power spectral density function was obtained by calculation the frequency response function of each model, and then low frequency power was computed. Cross spectral density function provided squared coherence and phase spectrum. Phase between the low frquency oscillation of the two signal was measured from the phase spectrum when the squared coherence is above 0.5. Results The advantage of using autoregressive model was that the power spectral density function was continous and sharp spectral peak was usually found. In patients with Rp/Rsor=0.25, there was no significant difference between the low frequency power of pulmonary artery pressure(384±461) and that of the systemic artery pressure(752±1241). In patients with Rp/Rs>or=0.25, it was more probable that low frequency oscillation of pulmonary and systemic artery pressure was timely coherent(sqaured coherence>0.5) than in patient with Rp/Rs Conclusion Autoregressive algorithm is a more powerful tool for spectral analysis than the method of conventional spectrum estimation. When pulmonary vascular resistance remains low, the low frequency oscillation of pulmonary artery pressure was negligible compared to systemic artery pressure. But as pulmonary vascular resistance elevates, the low frequency power of pulmonary artery pressure is much the same as that of systemic artery pressure, and there is a explicit time realtionship that pulmonary artery pressure leads the systemic artery pressure about 0~3 seconds in the low frequency range.
机译:背景技术全身动脉压的低频振荡被称为交感神经调节的标志。最近,报道了肺动脉高压患者的肺动脉压的低频振荡。但是,关于其定量关系和肺动脉压低频振荡与系统性动脉压之间的相位耦合,尚无进一步研究。使用自回归算法的功率谱分析和交叉谱分析是研究这些关系的有力工具。方法对31例室间隔缺损患者同时测量左肺和股动脉压力的模拟信号进行数字化并存储。在使用自回归算法对每个时间序列建模之后,通过计算每个模型的频率响应函数来获得功率谱密度函数,然后计算低频功率。互谱密度函数提供相干和相谱的平方。当平方相干高于0.5时,根据相位频谱测量两个信号的低频振荡之间的相位。结果使用自回归模型的优点是功率谱密度函数是连续的,并且通常会发现尖锐的谱峰。在Rp / Rsor = 0.25的患者中,肺动脉压的低频功率(384±461)和全身动脉压的低频功率(752±1241)之间没有显着差异。在Rp / Rs>或= 0.25的患者中,与Rp / Rs的患者相比,肺和系统动脉压力的低频振荡及时相干(保证相干性> 0.5)更有可能结论自回归算法是一种更强大的工具频谱分析比传统的频谱估计方法。当肺血管阻力保持较低时,与全身动脉压相比,肺动脉压的低频振荡可忽略不计。但是,随着肺血管阻力的升高,肺动脉压的低频功率与全身动脉压的低频功率几乎相同,并且存在明显的时间关系,即肺动脉压在较低的时间内领先全身动脉压约0〜3秒。频率范围。

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