Would you use a Wear OS app that learns whether you're standing, sitting, or lying down, etc.?
I've noticed that my Galaxy Watch counts steps and workouts well, but it completely ignores the fact that I spend hours standing still at work. As far as the watch is concerned, I'm just "inactive."
I'm thinking about building a Wear OS app that works differently.
The idea is:
Collect accelerometer, gyroscope, heart rate, step count, and other sensor data.
Estimate whether the user is standing, sitting, lying down, walking, or if the app is unsure.
When confidence is low, ask the user to confirm what they were doing.
Learn from those corrections over time so the model becomes personalized instead of using fixed rules.
Show daily and weekly totals like:
Standing: 5h 20m
Sitting: 3h 10m
Walking: 1h 15m
Initially I was thinking of using an LLM (OpenAI or Gemini) to analyze summarized sensor data, then eventually replacing it with a lightweight on-device model once enough labeled data is available.
My questions are:
Would this actually be useful to you?
Has anyone tried building something similar on Wear OS?
Do you think wrist sensors are sufficient for a personalized model after enough user feedback?
What features would make you install an app like this?
I'd love feedback before I start building.