Implementation of Fuzzy Logic in Managing Common Anesthesia

Abstract

Using fuzzy sets for reasoning is what we mean when we talk about fuzzy logic. Contradictory natures are prevalent phenomena in the medical field. Guidelines are used by anesthesiologists when taking care of patients. After gauging the patient’s vitals, he may make adjustments to the flow of medication and fluids, or even the ventilator settings. Knowledge about the real world is typically sketchy, inaccurate, and inconsistent. Due to the inherent representation of subjective human conceptions used in much medical decision making, fuzzy logic seems well-suited for use in anaesthesia. We have developed a fuzzy expert system using fuzzy methodology for the aim of fluid management during general anaesthesia. The desired intravenous fluid rate (IFR) is the defuzzified value that is output by the fuzzy expert system. Fuzzy inputs serve as antecedent parts of rules for a fuzzy expert system, and some examples of such inputs are mean arterial pressure (HUO), hourly urine output (HUO), and central venous pressure (CVP). It would only cost a little sum to have a human operator sometimes enter MAP, HUO, and CVP values into a personal computer for this purpose. The study’s overarching goal was to devise a method for approximating IFR by making use of a linguistic description of MAP and HUO. Fuzzy sets, including decreasing, constant, and growing MAP and HUO rates of change, would assist to illustrate the trend in a patient’s fluid state. To regulate fluid levels more precisely would be possible. Expert guidance in addition to the calculated use of fuzzy methods are essential for achievement of the desired outcome. Patients must be in generally good health before this mode may be used on them, and they must be undergoing minimally invasive surgery. Moderate to severe blood loss after surgery need more complex modalities involving more factors.