DEV Tutorial: Build a Custom Stress Score Engine Using Python and Raw PPG Signals

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A technical guide published on DEV Community explains how smartwatch stress scores work and shows developers how to replicate the underlying logic using Python. Most wearable stress scores rely on Heart Rate Variability (HRV), specifically the LF/HF frequency ratio, rather than simple heart rate counts. The tutorial walks through capturing raw PPG data via Bluetooth Low Energy using the Bleak library, then cleaning the noisy signal with a SciPy Butterworth bandpass filter. Developers are then shown how to extract R-R intervals, apply cubic spline interpolation for uniform sampling, and run a Fast Fourier Transform to calculate the final stress index. Compatible hardware includes devices like the Polar OH1 or a MAX30102 sensor paired with an ESP32 microcontroller.

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