Imagine a smart filter for heart scans that catches irregularities a human eye might miss. It works like a high-tech spell-checker for heartbeats, scanning signals from any device to spot trouble early. By using a massive library of heart patterns, it can predict future heart issues months before they happen.
Cardiovascular diseases are the leading cause of death globally, yet diagnosing complex arrhythmias is slow and often requires expensive, manual expert interpretation.
A hardware-agnostic, cloud-based AI platform that converts raw ECG signals into medical-grade reports and predicts heart disease behavior.
If you are a hospital network dealing with slow ECG interpretation and high diagnostic costs — this project developed a cloud-based AI platform that detects 22 arrhythmias with over 90% accuracy. This speeds up diagnosis and improves patient outcomes.
If you are a device manufacturer dealing with basic hardware that lacks advanced analysis — this project developed a hardware-agnostic AI engine that transforms raw signals into medical-grade reports. This allows your devices to integrate with a sophisticated diagnostic cloud.
If you are a pharma company dealing with the need for precise patient monitoring in clinical trials — this project developed an AI system capable of predicting Atrial Fibrillation. This provides a high-precision tool for tracking heart disease behavior over 6 months.
Based on available project data, the platform is offered as a SaaS (Software as a Service) model, though specific pricing tiers are not listed.
Yes, the system has already been validated with 22,482 patients across Spain and The Netherlands, significantly exceeding the initial target of 5,342.
The project utilizes a proprietary AI engine trained on one of the world's most comprehensive ECG databases and supports white-labelling for commercial scalability.
The platform has achieved CE marking as a Class IIa medical device and is currently pursuing FDA clearance.
The architecture is hardware-agnostic and designed to be integrable with any other eHealth platform as part of the clinical workflow.
The project is led by a single Spanish SME, Idoven 1903 SL, representing a 100% industry-led effort. This lean structure suggests a strong focus on commercialization and rapid deployment rather than academic research, as evidenced by the direct path to CE marking and FDA clearance.
Contact Idoven 1903 SL in Spain
Contact us to explore licensing opportunities for this CE-marked AI diagnostic tool.
