Analysis of parameters affecting blood oxygen saturation and modeling of fuzzy logic system for inspired oxygen prediction.

BACKGROUND AND OBJECTIVE

Fraction of Inspired Oxygen is one of the arbitrary set ventilator parameters which has critical influence on the concentration of blood oxygen. Normally mechanical ventilators providing respiratory assistance are tuned manually to supply required inspired oxygen to keep the oxygen saturation at the desired level. Maintaining oxygen saturation in the desired limit is so vital since excess supply of inspired oxygen leads to hypercapnia and respiratory acidosis which lead to increased risk in cell damage and death. On the other side a sudden drop in oxygen saturation will lead to severe cardiac arrest and seizure. Hence intelligent real time control of blood oxygen level saturation is highly significant for patients in intensive care units.

METHODS

This paper gives statistical pair wise analysis for finding out deeply correlated physiological parameters from clinical data for fixing fuzzy variables. An advisory fuzzy controller using Mamdani model is developed with R programming to predict FiO which is to be delivered from the ventilator to maintain SaO with in required levels.

RESULTS

Fuzzy variables for the fuzzy model is fixed using 75% of the clinical data collected. Remaining 25% of the data is used for checking the system. Compared the predictive output of the system with physicians' decisions and found to be accurate with less than five percentage error.

CONCLUSIONS

Based on the comparison the system is proved to be effective and can be used as assist mode for physicians for effective decision making.