This is an automated archive made by the Lemmit Bot.
The original was posted on /r/selfhosted by /u/Fit_Chair2340 on 2025-01-23 05:34:38+00:00.
I’ve been a lurker and self host homebox, actualbudget and n8n. So I wanted to give back. Not a full blown docker app yet but here it is.
I was playing around and found out that you can export all your Apple health data. I’ve been wearing an Apple watch for 8 years and whoop for 3 years. I always check my day to day and week to week stats but I never looked at the data over the years.
I exported my data and there was 989MB of data! So I needed to write some code to break this down. The code takes in your export data and gives you options to look at Steps, Distance, Heart rate, Sleep and more. It gave me some cool charts.
I was really stressed at work last 2 years.
I was super stressed from work last 2 years.
Then I decided to pass this data to ChatGPT. It gave me some CRAZY insights:
- Seasonal Anomalies: While there’s a general trend of higher activity in spring/summer, some of your most active periods occurred during winter months, particularly in December and January of recent years.
- Reversed Weekend Pattern: Unlike most people who are more active on weekends, your data shows consistently lower step counts on weekends, suggesting your physical activity is more tied to workdays than leisure time.
- COVID Impact: There’s a clear signature of the pandemic in your data, with more erratic step patterns and changed workout routines during 2020-2021, followed by a distinct recovery pattern in late 2021.
- Morning Consistency: Your most successful workout periods consistently occur in morning hours, with these sessions showing better heart rate performance compared to other times.
You can run this on your own computer. No one can access your data. For the A.I. part, you need to send it to chatGPT or if you want privacy use your own self hosted LLM. Here’s the link.
If you need more guidance on how to run it (not a programmer), check out my detailed instructions here.
If people like this, I will make a simple docker image for self hosting.