Circuit Implementation of Memristive Fuzzy Logic for Blood Pressure Grading Quantification

Abstract

Fuzzy logic can effectively deal with many uncertain problems due to its unique fuzziness and insensitivity to data, so it is widely used in health scenarios with precision grading quantification. Therefore, an analog circuit of memristive fuzzy logic for blood pressure grading quantification is designed in this paper. The circuit includes 1) fuzzifier module, 2) rule base module, 3) inference engine module. The fuzzifier module uses a memristor array to build a membership function circuit that can be fully programmed in parallel, and converts the input systolic and diastolic blood pressure signals into corresponding membership degrees through the circuit. The rule base module mainly implements fuzzy rules based on blood pressure fuzzy semantic sets through analog circuits. The function of the inference engine module is to transform the blood pressure rules stored in the rule base into the mapping relationship between fuzzy semantic sets, and to infer the results of blood pressure grading quantification. The PSPICE simulation results show that the calculation precision of the memristive fuzzy logic circuit can reach about 99.7%, and the accuracy rate of the circuit to achieve the blood pressure grading quantification reaches 98.69%. Compared to traditional digital circuits, this circuit has significant advantages in terms of power consumption and computational speed.