Prof. Dr.-Ing. Bert Arnrich


Intelligent Alarm Optimization for ICU's

Funded by the Federal Ministry of Education and Research.

In cooperation with AICURA medical, Charité – Universitätsmedizin Berlin, and idalab.

Bjarne Pfitzner, Jonas Chromik

The monitoring of vital signs in the intensive care unit (ICU) has significantly improved patient safety by alerting ICU staff when a parameter deviates from the normal range. However, up to 99% of these alarms are false-positive, resulting in desensitization of staff to critical alarms and several deaths per year.

The goal of the INALO project is to develop patient-specific and user-centered software based on Artificial Intelligence (AI) for the intelligent optimization of alarms generated by patient monitors. Alarms from the existing patient monitoring system in ICU can be prioritized in a patient-specific manner and false-positive alarms can be filtered out with the INALO system. For the development, available clinical data from the patient monitoring system and the electronic health record (EHR) will be combined and the latest advances in machine learning will be applied.

The intelligent combination of different data streams and subsequent AI-based processing will generate added value in patient treatment. With this approach, INALO is facing one of the central challenges of digitalization in medicine.

For more information, please visit the project's website: inalo.ai