Blood pressure regulation with RAS model and Q-learning control
by Ciprian Sandu
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 9, No. 1, 2017

Abstract: This paper focuses on the blood pressure regulation in post cardiac surgery patient, specifically on showing that Q-learning (a reinforcement learning method) is suitable for the automatic control of blood pressure in post cardiac surgery patients. It uses directly the clinical data; there is no need of a patient model. Such a model is used however, but only as a source of artificial clinical data. Firstly, we use this model in order to create closed-loop control with a classical PID controller and then with polynomial RST control (where a robustness analysis is performed). Secondly, as the contribution of this paper, we use the model only as a source of pseudo-clinical data with reinforcement learning, the Q-learning algorithm. In all these cases, the model contains the RAS reflex model of the body.

Online publication date: Mon, 26-Dec-2016

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