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一种基于流量依赖性反馈机制的动态脑自动调节新数学模型。

A new mathematical model of dynamic cerebral autoregulation based on a flow dependent feedback mechanism.

作者信息

Kirkham S K, Craine R E, Birch A A

机构信息

Faculty of Mathematical Studies, University of Southampton, Highfield, UK.

出版信息

Physiol Meas. 2001 Aug;22(3):461-73. doi: 10.1088/0967-3334/22/3/305.

Abstract

A new mathematical model representing dynamic cerebral autoregulation as a flow dependent feedback mechanism is presented. Two modelling parameters are introduced, lambda, the rate of restoration, and tau, a time delay. Velocity profiles are found for a general arterial blood pressure, allowing the model to be applied to any experiment that uses changes in arterial blood pressure to assess dynamic cerebral autoregulation. Two such techniques, thigh cuffs and a lower body negative pressure box, which produce step changes and oscillatory variations in arterial blood pressure respectively, are investigated. Results derived using the mathematical model are compared with data from the two experiments. The comparisons yield similar estimates for lambda and tau, suggesting these parameters are independent of the pressure change stimulus and depend only on the main features of the dynamic cerebral autoregulation process. The modelling also indicates that for imposed oscillatory variations in arterial blood pressure a small phase difference between pressure and velocity waveforms does not necessarily imply impaired autoregulation. It is shown that the ratio between the variation in maximum velocity and pressure variation can be used, along with the phase difference, to indicate the nature of the autoregulatory response.

摘要

提出了一种新的数学模型,该模型将动态脑自动调节表示为一种流量依赖性反馈机制。引入了两个建模参数,恢复率λ和时间延迟τ。针对一般动脉血压求出了速度分布,从而使该模型能够应用于任何利用动脉血压变化来评估动态脑自动调节的实验。研究了两种这样的技术,即分别产生动脉血压阶跃变化和振荡变化的大腿袖带和下体负压箱。将使用该数学模型得出的结果与来自这两个实验的数据进行比较。比较得出了相似的λ和τ估计值,这表明这些参数与压力变化刺激无关,仅取决于动态脑自动调节过程的主要特征。建模还表明,对于施加的动脉血压振荡变化,压力和速度波形之间的小相位差不一定意味着自动调节受损。结果表明,最大速度变化与压力变化之比可与相位差一起用于指示自动调节反应的性质。

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