Life data monitoring and analysis model for personalized healthcare

Abstract

As the focus of personal healthcare shifts from patient treatment to early detection and prevention, it is becoming increasingly important to manage personal wellness in our daily lives. Personal health monitoring of physical activities and status can be used to show users the distribution of their daily activities, making it easier for people to assess their health, adopt better lifestyles, and potentially decrease the occurrence of chronic diseases. In this paper, we propose a CA(5W1H)Onto-based life data monitoring model that provides basic monitored information from various devices and ensures preventive and proactive service for personalized healthcare. Additionally, we propose a life data analysis method to correlate the self-monitoring of activities with the status of the human body.