A Type-1 Diabetes simulator implemented in Python for Reinforcement Learning purpose

Documentation for setting up OpenAPS

Script written in TypeScript that uploads CGM readings from LibreLink Up to Nightscout.

The official implementation of the paper "Gluformer: Transformer-Based Personalized Glucose Forecasting with Uncertainty Quantification."

Here you can find a guide / tutorial on how to adapt a watchface to the needs of xdrip support. Main credit goes to Artem Kovalenko aka bigdigital.

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

Show your current blood sugar on the Windows Taskbar

The official implementation of the paper "GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks."

A simple discrete glucose traytip/tooltip for Nightscout under Windows, scripted with AutoIt

Integrate your LibreLink sensor data with Home Assistant

Rainmeter skin to display your Nightscout glucose on your Windows device using Rainmeter.

Client app to display blood glucose diagram from Nightscout site on Windows, Linux, OSX

There are over 450 millions of diabetic people all over the world. More shocking 1 out of 3 people don't even know they have diabetes. Diabetes either type 1 or 2 if not controlled can lead to serious health problems including blindness, heart disease, nerve damage, organ amputation. Controlling diabetes requires often monitoring of blood glucos…

Project to view Freestyle Libre 2 glucose readings in real-time on a Raspberry Pico

An sqlite3 schema for glucose sensor readings from Medtronic Minimed Carelink

Glucose Nightscout Add-on for Kodi

This repository provides an experimental and simplified setup for a non-continuous glucose monitoring system prototype using the NHS3152 development board, an NFC antenna, and electrochemical sensor.

Python Toolbox for glycaemic signal processing

GNU Gluco Control (GGC) is diabetes management application. It helps managing user's daily data, food data. It has graphs, statistics, reports, and a lot of diabetes devices support (meters, pumps, CGMSs). It works on any platform supporting at least Java 8 (1.8). We supports 3 languages, more can be added via Crowdin.