This project aims to build a health and fitness Android hybrid application that will provide personalized recommendations for each user based on the following data:
• Wearables Data (if users have Fitbit, our Android application will redirect them to Fitbit page for authorization)
• Nutrition Data (manual log from Food AI API & FatSecret API)
• Sleep Data (manual log from Fitbit API Google Fit API)
• Activity Data (manual log from Fitbit API Google Fit API)
Our project will integrate all the data from the different APIs (Fitbit, Google Fit, Food AI, FatSecret), and provide recommendations for users based on these data to give them insights on their health using analytics. Such insights are for each category like nutrition (e.g. important nutrients that is missing from diet according to week analysis). It also provides recommendations for factors that are correlated: activity, sleep, nutrition, mood and health (e.g. if a user has been having trouble sleeping or feeling depressed; possible link between diet and exercise on mood and diet on sleep) - our application will analyze all his relevant health data and come up with possible health risks (e.g. obesity, insomnia) and provide recommendations.
9Apps 4.9
