首页> 外文期刊>International Journal of Modelling, Identification and Control >Modelling arterial blood pressure waveforms for extreme bradycardia and tachycardia by curve fitting with Gaussian functions
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Modelling arterial blood pressure waveforms for extreme bradycardia and tachycardia by curve fitting with Gaussian functions

机译:通过高斯函数曲线拟合建模极端心动过缓和心动过速的动脉血压波形

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Arterial blood pressure (ABP) signal contains abundant information about heart beat rhythm and hemodynamic changes which can be employed to predict bradycardia and tachycardia. Thus, a waveform modelling method based on curve fitting is proposed to extract some significant difference between bradycardia and tachycardia. First, the ABP signal is pre-processed and is split into a series of single-period waveform. Then, a single-period ABP waveform model is proposed to describe the change of linear trend and waveform, and a nonlinear least squares method is employed to compute the parameters of the model. The bradycardia and tachycardia data from 2015 PhysioNet/CinC Challenge are engaged as experimental data. The results show that there are significant differences for many of the model parameters between bradycardia and tachycardia.
机译:动脉血压(ABP)信号包含有关心律和心律变化的大量信息,可用于预测心动过缓和心动过速。因此,提出了一种基于曲线拟合的波形建模方法,以提取心动过缓和心动过速之间的明显差异。首先,对ABP信号进行预处理,并将其分成一系列单周期波形。然后,提出了一种单周期ABP波形模型来描述线性趋势和波形的变化,并采用非线性最小二乘法来计算模型的参数。实验数据来自2015年PhysioNet / CinC Challenge的心动过缓和心动过速数据。结果表明,心动过缓和心动过速之间的许多模型参数存在显着差异。

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