Fuzzy Based User-Centric Smart Approach to Prevent Unhealthy Eating Habit Crisis

Abstract

Cholesterol plays a major role in keeping the human heart-healthy. High blood cholesterol is a key risk factor for cardiovascular diseases such as coronary heart disease and stroke. High blood cholesterol has become a severe health problem. The risk factors that affect a person's health cholesterol content include but are not limited to unhealthy diet, physical inactivity, high-stress status, genetic factors. However, many studies have discovered that there is a direct association between elevated levels of serum cholesterol and unhealthy eating habits. This problematic situation is influenced by busy lifestyles, a lack of time to pay attention to their meals, and a lack of knowledge about removing trans fats from daily diets. The primary goal of this study is to provide personalized guidance to prevent unhealthy eating habits via a mobile application. It allows to create a virtual food plate, analyze the risk status of that food plate, and predict a balanced diet as a replacement for the original food plate. The proposed approach uses an originally constructed food knowledge base and fuzzy logic to predict a balanced diet. Outcomes of the approach were tested using the interrater agreement manual method and obtained an accuracy of 80%. The computed Inter Rater Reliability (IRR) score was 75%, which shows the high reliability among the testers. Finally, this approach will assist people in self-controlling their cholesterol levels and prevent deadly heart diseases.