What Sticks Vision, Problem, and Approach

Vision

Provide empirically backed personalized health and wellness insights.

What Problem does it solve?

I believe dashboard/table of simple correlations showing what is correlated with better sleep can answer questions like:

• Does exercise affect my sleep?

• Does working out 2 hours one day provide better sleep than working out 15 mins the last 8 days?

• Does walking impact my sleep?

• Does temperature affect my sleep?

Furthermore, and perhaps most importantly, we can tell which one affects sleep most.

While this might not be conclusive, it is far better than relying on averages or anecdotal evidence found in health and wellness websites.

Approach

We can do this with a table – dashboard of linear correlations. Ultimately delivered to user by phone applications. I can build the iOS app.

This data will be populated by an API suite that connects to the various data sources and does the calculations. I am using Python. I can use help on this.

A user friendly phone app will communicate with the API’s to get user data and create the dashboard similar to seen on the video.

General Overview of the What Sticks API Suite

Data Collection Endpoints

There will be a set of API endpoints that when called included user credentials, that when called return user data and stores it in a database.

For example I have Oura Ring, so I will make and endpoint that receives the user’s credentials. Then calls Oura Ring API for the user’s data. Then stores the data in the What Sticks Database.

I also use Polar exercise monitoring. And these type of API endpoints will be built for Fitbit, Strata, etc.,

Data Analysis Endpoints

Then there will be an endpoint that is called by the phone app. This one does the correlation table calculations. This occurs by connecting to the What Sticks Database and running the math and returning a json file to the phone app that contains all the correlations.