Members of the state parliament Schmitz and Franz visit the TU
etit scientists present their research
2024/09/30 by as / sas
In September, Lucas Schmitz and Peter Franz from the Hessian State Parliament visited TU Darmstadt. The visit focussed on TU Darmstadt's diverse contributions to shaping the future. Two etit scientists were invited to present their research work.
In September, members of the Hessian state parliament Lucas Schmitz (spokesperson for science and art) and Peter Franz (MP for the Darmstadt II constituency; both CDU) were guests at TU Darmstadt. They were welcomed to the Science Palace by TU President Tanja Brühl and TU Chancellor Martin Lommel. The visit focussed on the diverse contributions that TU Darmstadt is making in research, teaching and xchange to shaping the major tasks of the future.
The visitors and members of the Executive Board also discussed the question of how TU Darmstadt's formative role as a driver of innovation for the region and Hesse can be further promoted. In dialogue with scientists from the university, Franz and Schmitz were able to gain an impression of the diversity of the university's research projects through two interactive presentations.
Sebastian Dill and Jaid Haidamous from the , which is headed by Prof. Dr.-Ing. Christoph Hoog Antink, at the etit faculty presented several projects in which contactless, AI-based measurement technology is being developed to support both users and people working in the healthcare sector. The guests were able to test the practical application of two tools live on site. Artificially Intelligent Medical Systems Lab
The first is camera-based pulse measurement. By changing the subject's skin colour, which correlates with the pulse rate, a pulse can be derived using this method without having to attach sensors directly to the body. Camera-based movement analysis, the second tool presented, can be used, for example, to improve the success of physiotherapy treatment. The patient can perform exercises in a controlled manner at home: The patient's own movement pattern can be compared in real time with the one defined in advance by the therapist.
Finally, Dill and Haidamous gave an insight into a cooperation project with the University Hospital Frankfurt as part of the RMU Alliance, which aims to improve the localisation of epileptic seizures using a deep-learning-based tool.
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