Semiconductor chip with integrated artificial intelligence detects heart diseases

© Fraunhofer IMS
Schematic representation of how the miniaturized ARTEMIS system works. The AI analysis for the evaluation and classification of patient data helps to maintain the health of the patient and at the same time leads to a relief of the medical staff.
© Fraunhofer IMS
Fraunhofer IMS as exhibitor at COMPAMED 2021

With almost two million people affected, atrial fibrillation (AF) is one of the most widespread diseases in Germany. AF that is detected too late can have fatal consequences for patients, such as a stroke. Such severe consequences could be avoided by early intervention.

With significant participation of the IMS, the "ARTEMIS" consortium aims to provide efficient, digital healthcare for this disease.

The main innovation consists of miniaturized ECG electronics based on artificial intelligence (AI), which detects atrial fibrillation in real time directly at the patient.

Through AI data analysis established in a semiconductor circuit - and software, critical changes in the ECG are detected. The results are quickly and securely transferred to the electronic patient record using the 5G standard.

AI" supports by analyzing and processing large amounts of data and providing decision support. Based on the pre-analysis of the patient data, the medical staff is alerted at an early stage to a potentially life-threatening situation and can interact accordingly.

The feasibility of detecting cardiac arrhythmias using machine learning has already been demonstrated very successfully by the scientists at the IMS. The low energy requirements of the IMS concept make it possible to create a particularly small monitoring system, which increases wearing comfort and patient acceptance.

The consortium includes experienced distributors, manufacturers and medical service providers who will ensure targeted commercialization after the 3 years of the research project. The consortium leader is getemed Medizin- und Informationstechnik AG. Other project participants are Charité - Universitätsmedizin, CYIENT GmbH and SYNIOS GmbH.

The project is funded by the BMBF under the grant number 13GW0579D.