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Intelligent Alarm Optimizer

The INALO project is funded by the BMBF as part of the KMU Innovativ funding program. Within the project, we develop a user-centered platform that will enable research and implementation of alarm optimization approaches for patient monitoring in the ICU by means of patient-specific data and machine learning approaches. In doing so, the perspective is to achieve a reduction of unnecessary alarms.

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Patient safety has improved significantly in recent decades due to the monitoring of vital signs in intensive care units (ICU). However, between 72 and 99% of these alarms are described as false positives or "non-actionable". They can trigger "alarm fatigue," a desensitization of staff to critical alarms that can even lead to patient harm and even death.

Innovations and perspectives

Digital documentation generates several gigabytes of health data every day. This data can already be used as a basis for artificial intelligence (AI) algorithms that support patient care in the ICU. The development of an alarm optimizer could promote a better understanding of the alarm situation, as well as reduce the workload of ITS staff and improve patient care by reducing unnecessary alarms.

Project duration

2020-09 to 2024-06


PD Dr. med. Akira-Sebastian Poncette

Section Medical Data and Systems (IMI)

Project website

You can reach the project website at (currently only available in German).

Project video