Estimation of blood pressure parameters using ex-Gaussian model
Artur Poliński, Tomasz Kocejko
Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 1427–1430 (2016)
Abstract. The paper presents example of model-based estimation of blood pressure parameters (onset, systolic and diastolic pressure) from continuous measurements. First, the signal was low pass filtered and its quality was estimated. Good quality periods were divided into beats using electrocardiogram. Next, beginning of the each beat of the blood pressure signal, was approximated basing on the function created from sum of two independent distributions: Gaussian and exponential. The nonlinear least square method was used to fit measurement data to the model. The initial conditions for the fitting procedure were selected for each beat basing on its parameters. Finally, the diastolic and systolic values of blood pressure and onset were determined.
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