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HappyApp

Explainable mood inference from physiological data

Now live at: https://swacziarg.github.io/HappyApp/#/login

HappyApp is a secure, multi-user web app that converts raw Garmin health data into personalized, explainable daily mood predictions.


What it does

  • Users upload Garmin exports (ZIP / JSON)
  • Backend ingests and normalizes physiological data
  • Personalized baselines are computed per user
  • Daily features are inferred into a mood score (1–5)
  • Users can add manual mood check-ins
  • A React UI displays today’s mood and historical trends

High-level flow

Garmin Export → Ingestion → Daily Features (personal baselines) → Mood Inference (rule-based) → Predictions API → React UI


Tech stack

Backend: FastAPI, Supabase (Postgres + RLS)
Frontend: React
Auth: Supabase Auth (JWT)
Deployment: Render + GitHub
Data: Garmin exports (sleep, HRV, stress, activity, body battery)

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Project to track mood based on garmin data

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