Wearable Sensor Stress Detection w/ Spotify
A machine-learning system that detects stress from wearable biometrics and responds with adaptive music.
Overview
Your body knows you're stressed before you do. This project turns that physiological signal into action — detecting stress from wearable biometrics and responding with music tuned to bring you back down.
I built an ML pipeline that ingests wearable sensor streams, engineers features from heart-rate and related signals, and classifies stress states in near real time, then connected it to the Spotify API to trigger calming, adaptive playlists.
The result is a closed loop: sense, decide, respond — a working prototype for biometric-driven music therapy that reacts in the moment instead of after the fact.
At a glance
Stress is continuous and physiological, but most interventions are manual and arrive far too late.
An ML pipeline that classifies stress from wearable sensor signals and integrates with Spotify to trigger calming, adaptive playlists.
A closed-loop wellness prototype that senses stress and responds in the moment with music therapy.
Highlights
- Stress classification from wearable biometric signals
- Feature engineering on heart-rate and related streams
- Spotify API integration for adaptive music therapy
- Closed-loop sense-and-respond prototype