A implementação da lógica Fuzzy na filtragem de sinais em aparelhos de pressão sanguínea e sua possível evolução

Abstract

This work addresses the application of Fuzzy logic techniques to noise filtering in blood pressure signals obtained from automatic sphygmomanometers. The central problem lies in the presence of noise and distortions in the oscillometric pressure signals, which compromise measurement accuracy and clinical diagnosis. The main objective is to develop and compare methods based on Fuzzy logic, such as Fuzzy C-Means, Fuzzy inference systems, Fuzzy TOPSIS, and Fuzzy rules, in order to improve the quality of processed signals. This research is justified by the growing demand for more reliable and accessible medical devices, considering that the accuracy of blood pressure readings is crucial for public health. The methodology involved generating blood pressure signals with predetermined noise levels, implementing the fuzzy methods in a simulation environment, and evaluating the results based on performance metrics established by the AAMI standard. The final considerations indicate that certain fuzzy approaches demonstrated effective noise reduction capabilities, with significant improvements in error metrics, highlighting their potential for application in non-invasive blood pressure measurement systems.