Hey everyone,
Like many of you here, I'm a big Apple Watch user and love the amount of health data it collects. For a while though, I felt I wasn't getting the full story from the raw numbers in Apple Health. I wanted to go deeper, understand the connections, and get more personalized guidance on how to optimize my workouts and overall wellness.
As a uni student studying Machine Learning, I decided to tackle this by building my own iOS app, Thryve Wellness:
https://apps.apple.com/us/app/thryve-wellness/id6737707259
to try and unlock more of that potential. My goal was to create something that:
It's been a challenging but rewarding solo project alongside my studies, built entirely with Swift and SwiftUI. The aim is to provide a more analytical companion for serious Apple Watch users who want to turn their rich data into truly actionable insights.
I'd be really interested to hear how other Apple Watch users here approach analyzing their health data beyond what the stock apps offer.
Cheers,
Seb
Like many of you here, I'm a big Apple Watch user and love the amount of health data it collects. For a while though, I felt I wasn't getting the full story from the raw numbers in Apple Health. I wanted to go deeper, understand the connections, and get more personalized guidance on how to optimize my workouts and overall wellness.
As a uni student studying Machine Learning, I decided to tackle this by building my own iOS app, Thryve Wellness:
https://apps.apple.com/us/app/thryve-wellness/id6737707259
to try and unlock more of that potential. My goal was to create something that:
- Offers Personalized Workout Optimization: Instead of just generic heart rate zones, Thryve analyzes your past Apple Watch workouts (intensity, duration, frequency, pace from HealthKit) to help identify your optimal parameters to maximize impact on specific goals (like improving a calculated Fitness Score, or minimizing Stress Impact). It gives tailored feedback after sessions.
- Uncovers Deeper Correlations (with Time Lags): I was fascinated by how different metrics might influence each other over time. So, Thryve can look for correlations between, say, your sleep quality from the Watch and your HRV or stress levels not just on the same day, but 1, 2, or even 3 days later. It's been interesting to see those delayed effects pop up from the data.
- Provides Transparent Wellness Scores: It calculates scores for Overall Wellness, Sleep, Fitness, etc., but also shows which HealthKit metrics are contributing most to those scores and their changes, so it's not just a "black box" number.
- Keeps Data 100% Private: All this analysis happens directly on the iPhone using the HealthKit data. No accounts, no cloud servers for the health data.
It's been a challenging but rewarding solo project alongside my studies, built entirely with Swift and SwiftUI. The aim is to provide a more analytical companion for serious Apple Watch users who want to turn their rich data into truly actionable insights.
I'd be really interested to hear how other Apple Watch users here approach analyzing their health data beyond what the stock apps offer.
- What insights are you currently trying to extract?
- Are there specific correlations or optimization questions you wish were easier to answer using your Watch data?
- What are your go-to methods or third-party apps for deeper analysis?
Cheers,
Seb