There are 3 repositories under glucose-monitoring topic.
A Type-1 Diabetes simulator implemented in Python for Reinforcement Learning purpose
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
Client app to display blood glucose diagram from Nightscout site on Windows, Linux, OSX
An sqlite3 schema for glucose sensor readings from Medtronic Minimed Carelink
The official implementation of the paper "GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks."
Allows easy use of the Dexcom Share API in your JavaScript project. Originally based on pydexcom.
eGluco is an app that allows you to measure your glucose levels non-invasively when connected to it's respective device. The device is curently being developed in UDESC-CCT. You can find the app in Play Store.
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 glucose level which can be either done at hospital or with personal glucometer kit. In both cases blood sample needs to be drawn from the body. Doing glucose test several times a day is obviously painful, moreover more check your glucose better you can control and continuous monitoring of glucose can lead to maximum flexibility to control it. This project aims at open source non-invasive glucometer where people no longer need to draw blood samples in order to measure it. Many attempts have been made to make it happen but none of those came out as a real product. In this approach I'm trying Machine Learning (Artificial Intelligence) and a new sensor to make it happen, currently it's in development stage. My solution includes a custom hardware packed with new sensor and an embedded processor and a firmware software. Machine Learning algorithm is being optimized so that it can run smoothly in the embedded processor.
App programmed in Swift/SwiftUI for using Libre blood glucose sensors.
Project to view Freestyle Libre 2 glucose readings in real-time on a Raspberry Pico
CGMShiny is an R Shiny application for analyzing Continuous Glucose Monitor data. Primarily intended for use in research studies and dietary interventions.
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.
eGluco is an app that allows you to measure your glucose levels non-invasively when connected to it's respective device. The device is curently being developed in UDESC-CCT. You can find the app in Play Store.
Integrate your LibreLink sensor data with Home Assistant
Final project for the course Deep Learning at DTU. Further continuation of the project with the Food Science department at KU.
clock face that displays blood glucose information from libre2system via librelinkup
This project intends to implement and expand upon the color density Poincare Plot representations of CGM data detailed in Glucose-at-a-Glance by Henriques, et al. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4455408/
An Android application allows to store the measurements of blood glucose levels in google spreadsheet
Functions to calculate glucose summary metrics, glucose variability metrics (as defined in clinical publications), and visualizations to visualize trends in CGM data. (In R)
Python script for downloading measurements from a Beurer GL50 EVO glucose meter using USB