Functions to calculate glucose summary metrics, glucose variability metrics (as defined in clinical publications), and visualizations to visualize trends in CGM data.

Functions to extract features from wearable data to track and predict infectious disease status.

Are you ready to FLIRT with your wearable data?

Deep Learning Methods for Identifying Human Postures from Hip-Worn Accelerometer Data

Devicely: A Python package for reading, timeshifting and writing sensor data

A Python package to interact with fasting logs from apps like Zero.

Functions to calculate glucose summary metrics, glucose variability metrics (as defined in clinical publications), and visualizations to visualize trends in CGM data. (In R)