We have all this data on ourselves and our health but how are we using it for ourselves?
The idea behind the health tracker is to piggyback off of existing sensors and data that our phones and wearables can have as well as self-reported user data in order to come to understandings about our own health that can directly inform our daily decisions to better steer us towards personalized.
Many people suffer from food and environmental allergies, but sometimes go for years without knowing what. Often elimination diets are the only thing that can inform these decisions since allergen tests are not accurate. By combining self-reported data and information passively collected from smartphones, this app vwould use pattern recognition with passive and active data in order to come to conclusions about what sort of potential environmental or food triggers are affecting a users health.
The app would be able to learn over time that pain or headaches are worse depending on the weather patterns, on trips to certain restaurants, or when eating certain foods or exercising a certain amount. We think very short term in a 2-3 day window but sometimes allergens can affect us for weeks at a time and there can be a lag period before symptoms start, for example in the case of acne based off of eating foods. This makes it very difficult for us to understand what is causing these symtoms.
Winner of the 1st place prize at the University Innovation Fellows Regional "Mile High Meetup" Hackathon .