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Model identification of the neural control of the cardiovascular system using NARMAX models

机译:使用NARMAX模型识别心血管系统神经控制的模型

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The neural control of the human cardiovascular system has been modeled using a NARMAX (non-linear autoregressive moving-average model with exogenous inputs) model, and compared with MA (moving-average) model and an ARMAX (autoregressive moving-average model with exogenous inputs) model. In these approaches, models are sought in the form of difference equations with unknown parameters to be estimated on the basis of input-output data. The input variable considered has been the carotid-sinus blood pressure and five output variables have been analyzed: heart rate control, peripheral resistance control, myocardial contractility control, venous tone control, and coronary resistance control. Results obtained show that NARMAX models present a better fit than the ARMAX models.
机译:已使用NARMAX(带有外源输入的非线性自回归移动平均模型)模型对人类心血管系统的神经控制进行了建模,并与MA(移动平均)模型和ARMAX(具有外生输入的自回归移动平均模型)进行了比较输入)模型。在这些方法中,以具有未知参数的差分方程的形式寻找模型,以基于输入-输出数据进行估计。所考虑的输入变量是颈动脉窦血压,并分析了五个输出变量:心率控制,外周阻力控制,心肌收缩力控制,静脉张力控制和冠状动脉阻力控制。获得的结果表明,NARMAX模型比ARMAX模型具有更好的拟合度。

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