Fuzzy Logic-based Risk Assessment Framework to Evaluate Physiological Parameters

Nowadays the patient monitoring systems are more and more widely used due to the advances in the technical background. These systems can improve the quality of life and by using them, several complications can be avoided in emergency situations. Nevertheless, the proper evaluation of the measured factors is a highly problematic task. The medicine uses a number of parameters, which are difficult to quantify, the boundaries of the examined risk factors cannot be given in a general form, the realistic result is only available from personalized thresholds. For these reasons, user-specific evaluation is required as much as possible, which uses individual characteristics, also the living conditions, habits and the medical recommendations taken into account during the risk calculation. In addition, the complex interactions between the input factors, which are often opaque, can be better handled in a patient-specific way based on the medical history of the patient or previous measurements. We developed a risk assessment framework to meet the above mentioned requirements. This system is flexible with a high degree of adaptive capacity. For the sake of ease of extensibility, and in order to achieve transparency, a generalized, modular system structure is implemented, which is joined with a database to specify the parameters of the configurable subsystems.