Optimal Design and Internet of Things Implementation of a General Type-2 Classifier for Blood Pressure Levels

Abstract

Recently, soft computing techniques, such as Type-2 Fuzzy logic and bio-inspired algorithms have been utilized in many areas. In this work, we propose a medical diagnosis application using type-2 fuzzy logic and the Ant Lion Optimizer to classify the blood pressure levels. We utilized the Framingham database for the optimization of the classifier. The main contribution of this work is to develop an intelligent model to classify the blood pressure levels and its Hardware Implementation using the Internet of Things concept on the Jetson Nano Board. This implementation utilized a blood pressure level monitor to obtain the systolic and diastolic blood pressure of the patients, which are the inputs of the classifier. The classification results and the input parameters can be monitored locally in a Human Machine Interface display or can be monitored in any other place through the internet of things concept. The results demonstrate that Type-2 Fuzzy logic achieves better results than Type-1 Fuzzy logic.