A FUZZY LOGIC BASED EXPERT SYSTEM FOR DETERMINATION OF HEALTH RISK LEVEL OF PATIENT

Monish Kumar Choudhury, Neelanjana Baruah

Abstract: The aim of this study is to design a fuzzy expert system for calculating the health risk level of a patient. The fuzzy logic system is a simple, rule-based system and can be used to monitor biological systems that would be difficult or impossible to model with simple, linear mathematics. The designed system is based on the modified early warning score (MEWS).The system has 5 input field and 1 output field. The input fields are blood pressure, pulse rate, SPO2 ( it is an estimation of the oxygen saturation level in blood. ), temperature, and blood sugar. The output field refers the risk level of the patient. The output ranges from 0 to 14. This system uses Mamdani inference method. A larger value of output refers to greater degree of illness of the patient. This paper describes research results in the development of a fuzzy driven system to determine the risk levels of health for the patients. The implementation and simulation of the system is done using MATLAB fuzzy tool box.

Keywords: Fuzzy logic, The Modified Early Warning Score (MEWS), Physiological Parameters, Classification of Vital Signs, MATLAB Tool, Fuzzy Inference System, Fuzzification, Defuzzification

DOI: https://doi.org/10.15623/ijret.2015.0405049