Research

Smart Wound Dressing incorporating Dye-based Sensors

In Germany alone, the number of patients with chronic wound healing disorders is estimated at around 2.7 million. The aim of the SWODDYS project is to research the fundamentals for a new type of intelligent wound dressing for the treatment of acute and chronic wounds, which can monitor the energy-metabolic tissue and wound healing status individually for each patient and online by integrating fluorescent dye-based oxygen, pH and CO2 sensors. 

This project is done in collaboration with PreSens, the University Hospital Regensburg, and Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) (Research group: Machine Learning and Data Analytics (MaD) Lab, Department AIBE) and is funded by the Bayerische Forschungsstiftung.

Diabetes Management

Research goals in this field are to improve blood glucose forecasting and nocturnal hypoglycemia prediction considering 1) data of children, 2) effect of previous physical activity) and 3) deep learning and basic machine learning approaches.

This project is done in cooperation with Universitäts-Kinderspital beider Basel and ETH Zürich (Research group: Medical Data Science).