Personal health tracking using mobile devices

Health tracking is considered as one of the most important activities in our daily life. In this project, we mainly focus on developing a personalized mobile application for people to collect their daily food intakes, sleep quality, and pressure rating (psychological) data. By analyzing these daily statistical data, we can assess  how food impacts our health. There are many applications on the market that serve the same common functions of health tracking (nutrition facts, weight, etc.); however, our application has two new interesting features, particularly in reference to sleep quality and  ressure ratings. By incorporating these two new features, we found a certain number of daily intake calories increased along with the change of daily pressure and sleep quality. All of these data will be analyzed further using Machine Learning techniques in order to find their relationships for weight prediction.