Seamless Health Data Integration, Exploration and Motivation

Inspiration

I was inspired to synthesize fitness data analysis with forecasting as a challenge based on prior interest in fitness challenges and recent experiences with a forecasting internship. See the code at https://github.com/jamesyoung93/SanfordHealthHack2020.

What it does

This app takes your exported health data from Apple Health apps including the Apple watch and turns it into interactive visualizations for exploring your health, forecasts, challenges, and reflection on recent performance.

How I built it

I built this app using the open-source language "R" and its web-app framework "shiny". I

Challenges I ran into

It would be a challenge to integrate the example Apple Health data I have used in this app with an EMR. The example Apple Health data may not line up with the health outcomes of the EMR data in an intuitive way because they are different "example persona" data.

Accomplishments that I'm proud of

I am proud that I completed this submission in addition to my other day-to-day responsibilities including work, class, teaching, and research as a grad student at SDSU.

What I learned

I learned that Apple Health data, the type that my chosen "persona" wanted to share, is actually relatively easily extracted and can be analyzed in insightful ways in R. This fitness data may have cross-over with health outcomes and may inform healthcare guidance with further availability and study.

I also learned that screen capture for windows doesn't transition as you click, however, I learned this too late.