AI-based Biosignal Analysis

AI-based Biosignal Analysis

Biosignals support physicians in their diagnostic work by providing information about the patient’s state of health, thus enabling them to draw diagnostically relevant conclusions. To do this, the data that biosensors generate must be reliably recorded and analyzed. For example, motion artifacts must not influence the interpretation of the data, so that a reliable diagnosis can be made on the basis of a constant level of data quality.

In reality, the metadata obtained from mobile devices and the quantities of data from studies represent an enormous challenge – how is this data to be interpreted and used intelligently?

To close this gap, we offer you licensing for existing algorithms and the development of basic AI algorithms tailored precisely to your needs. Give us a call – we would be happy to find a solution for you!


AI-based multimodal data analysis

Use of AI-based methods for signal analysis from multimodal parameters (e.g. blood pressure, heart rate), anamnesis data and laboratory findings from other disciplines


AI-based analysis of biosignals from wearables

Using AI-based algorithms, analyze and process biosignals quickly, reliably, energy-efficiently and without motion artifacts


Affective Sensing

Adaptive Systems for a Better Daily Living Environment


Project »ERIK«

Robots as physical interaction partners and development tools


ADA Lovelace Center for Analytics, Data and Applications

New competence center for data analytics and AI in industry
The ADA Lovelace Center uniquely combines AI research with AI applications in industry. Here the partners can network with each other, benefit from each other's know-how and work on joint projects


Energy-efficient AI system

Fraunhofer participates in Germany’s Sprunginnovationen competition with the ADELIA project