Guzzetti S, Signorini M G, Cogliati C, Mezzetti S, Porta A, Cerutti S, Malliani A
Centro Ricerche Cardiovascolari del CNR, Medicina Interna II, Università di Milano, Italy.
Cardiovasc Res. 1996 Mar;31(3):441-6.
Heart rate variability (HRV) is characterised by a variety of linear, non-linear, periodical and non-periodical oscillations. The aim of the present study was mainly to investigate the role played by neural mechanisms in determining non-linear and non-periodical components.
Analysis was performed in 7 recently heart transplanted patients and in 7 controls of similar age whose HRV signal was collected during 24 h. Parameters that quantify non-linear dynamic behaviour, in a time series, were calculated. We first assessed the specific non-linear nature of the time series by a test on surrogate data after Fourier phase randomization. Furthermore, the D2 correlation dimension, K2 Kolmogorov entropy, and H self-similarity exponent of the signal were estimated. From this last parameter, the dimension D = 1/H can be obtained. In order to assess whether the dynamics of the system are compatible with chaotic characteristics, the entire spectrum of Lyapunov exponents was calculated. We used return maps to graphically represent the non-linear and non-periodical behaviours in patients and controls.
Surrogate data suggest that the HRV time courses have unique non-linear characteristics. D2, K2 and 1/H parameters were significantly lower in transplanted subjects than in controls. Positivity of the first Lyapunov exponent indicates divergence of trajectories in state-space. Furthermore, the display of return maps on projections obtained after Singular Value Decomposition, especially in low-complexity data (as in transplanted patients), shows a structure which is suggestive of a strange attractor. These findings support the hypothesis that chaotic dynamics underlie HRV.
These results indicate that non-linear dynamics are likely to be present in HRV control mechanisms, giving rise to complex and qualitatively different behaviours. System complexity decreases in transplanted patients and this may be related to loss of the neural modulation of heart rate.
心率变异性(HRV)具有多种线性、非线性、周期性和非周期性振荡特征。本研究的主要目的是探讨神经机制在决定非线性和非周期性成分中所起的作用。
对7例近期接受心脏移植的患者和7例年龄相仿的对照组进行分析,收集他们24小时的HRV信号。计算了量化时间序列中非线性动态行为的参数。我们首先通过傅里叶相位随机化后的替代数据检验评估时间序列的特定非线性性质。此外,还估计了信号的D2关联维数、K2柯尔莫哥洛夫熵和H自相似指数。从最后一个参数可以得到维数D = 1/H。为了评估系统动力学是否与混沌特征相符,计算了李雅普诺夫指数的全谱。我们使用返回映射以图形方式表示患者和对照组的非线性和非周期性行为。
替代数据表明HRV时间进程具有独特的非线性特征。移植受试者的D2、K2和1/H参数显著低于对照组。第一个李雅普诺夫指数为正表明状态空间中轨迹的发散。此外,在奇异值分解后得到的投影上显示返回映射,特别是在低复杂度数据中(如移植患者),显示出一种暗示奇怪吸引子的结构。这些发现支持了HRV背后存在混沌动力学的假设。
这些结果表明非线性动力学可能存在于HRV控制机制中,从而产生复杂且性质不同的行为。移植患者的系统复杂性降低,这可能与心率神经调节的丧失有关。