Modelling arterial blood pressure waveforms for extreme bradycardia and tachycardia by curve fitting with Gaussian functions

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.