Analysis of Android-based Body Health Monitoring System Results using Fuzzy Mamdani Method

Abstract

In a health monitoring system, an Android-based Health Detector (AHD) application uses fuzzy Mamdani to detect health concerns. The data given can be used as an input for multi-sensor readings produced from physiological health detection. The body's total health is determined when the detected health is merged with the fuzzy Mamdani algorithm. Anger, apathy, and apathy were calculated as variables. The fuzzy Mamdani method to body health problems involves creating fuzzy sets, applying implications functions, and synthesizing rules. This study found that aging affects both men's and women's health. Persons over 65 are more likely than younger people to suffer health issues, even if only a minority of them have been diagnosed. The fuzzy Mamdani technique had a high accuracy rate of 93.33 percent in this study.