M-Health of Nutrition: Improving Nutrition Services with Smartphone and Machine Learning

Abstract

Balanced and adequate nutrient intakes are increasingly desired for people, especially those affected by chronic diseases. How to help people to realize appropriate nutrient consumption is an issue that should be addressed in smart healthcare. This study proposes a novel smartphone-based platform that includes dietary records, nutrition data analysis, and online nutritional guidance to improve remote nutrition services. Positive results from a trial conducted in cooperation with a hospital confirm the platform's promising capabilities in nutrition guidance and disease management. Additionally, to explore how nutrient intake impacts human health, this study took the relationship between hypertension and nutrient intake, and personal information as a case study. The findings indicate that our platform can provide detailed nutrient analysis services, and machine-learning-based prediction methods can accurately predict the user's blood pressure with little error.