If you are a clinic dealing with high patient readmission rates due to missed deteriorations — this project developed an AI-driven remote observation model that monitors patients 24/7. This allows for immediate reaction to health drops rather than waiting for the next appointment.
AI-Powered Continuous Remote Monitoring System for Chronic Disease Management
Imagine if doctors could watch a movie of your health instead of just looking at a few photos taken during a clinic visit. This system uses a wearable wristband and AI to track vital signs 24/7, catching dangerous health drops before they become emergencies. It turns a few random check-ups into a constant stream of health data that alerts medics in real-time.
What needed solving
Healthcare relies on 'snapshot' examinations that miss critical patient deteriorations. This leads to preventable deaths and inefficient emergency responses for chronic and critical patients.
What was built
An AI-powered remote observation system including a custom bracelet with SpO2 and temperature sensors, a data homogenization database, and retrained AI algorithms for chronic disease biomarkers.
Who needs this
Who can put this to work
If you are a device maker dealing with fragmented data from spot-check tools — this project developed a new database and bracelet design that homogenizes high-resolution data. It enables flexible transmission from 10-minute intervals to real-time streaming.
If you are an insurer dealing with the high cost of emergency interventions for chronic patients — this project developed a system already used for 50,000 critically ill patients to prevent deaths. Shifting to this continuous model reduces expensive emergency hospitalizations.
Quick answers
What is the cost or pricing model for this solution?
Based on available project data, specific pricing or cost structures are not disclosed.
Can this system be scaled to a large number of patients?
Yes, the model has already been implemented for more than 50,000 critically ill patients.
What is the status of the IP and licensing?
The project has performed an updated Freedom to Operate (FTO) analysis to ensure the legal viability of the technology.
How does the system integrate with existing medical hardware?
It uses a new database to homogenize information from spot-check medical devices and high-resolution data units.
What is the timeline for the current development phase?
The project period runs from 2023-08-01 to 2025-07-31.
Who built it
The project is led by Check Point Care Ltd, a Bulgarian SME. The consortium is highly streamlined and industry-focused, consisting of 3 partners, all of whom are SMEs (100% industry ratio). This suggests a strong drive toward commercialization rather than academic research.
Contact Check Point Care Ltd in Bulgaria
Talk to the team behind this work.
Contact us to explore licensing opportunities for the ARCHANGEL AI monitoring core.