STATE ESTIMATION AND STOCHASTIC CONTROL OF THE BODY TEMPERATURES OF A NEONATE USING THE PARTICLE FILTER MODEL PREDICTIVE CONTROL

This work deals with the cooling treatment of the hypoxic-ischemic encephalopathy in neonates. This is a neurological disorder characterized by the lack of oxygen (hypoxia) and low blood flow (ischemia) in the affected tissue (mainly brain). For the last few years, the main treatment for hypoxic-ischemic encephalopathy in neonates has been the mild hypothermia. Although the neurological protective effects of the cooling treatment are not completely understood, it is known that brain damages caused by ischemia are reduced with low temperatures. In this computational work, the geometric model as well as the blood pool concept were based on Fiala's model. Pennes' equation was applied in each body segment for the solution of the bioheat transfer problem. The combined application of the particle filter method and stochastic model predictive control is presented to control the body temperatures of a neonate. Results are presented for input data typical of newborns undergoing local cooling treatment.