On February 12th, 2024 at 2.30 pm the seminar "Can't Touch This! - Unobtrusive Sensing using Artificial Intelligence" will take place at Dipartimento di Elettronica, Informazione e Bioingegneria, BIO1 Room (Building 21).

A common theme of many science-fiction scenarios is that the physician of the future seems to be able to wirelessly scan a person and determine his or her health status without physical interference. A common theme of today’s diagnostics is the use of invasive procedures, stationary devices, wires, adhesive-based connections, and the associated limitations in flexibility and comfort. At the same time, the development of sensing modalities for unobtrusive sensing is ever increasing, both in the scientific community as well as in the industry. In part, this ever-accelerating development is fueled by the developments in artificial intelligence. In this talk, we will explore how artificial intelligence, in particular machine learning, sensor fusion, and computer vision may be used to extract diagnostic information using cameras and other types of unobtrusive sensors.

Christoph Hoog Antink received the M.S. degree in mechanical engineering from the University at Buffalo, USA, in 2011, and the Dipl. Ing. and Dr. Ing. (Ph.D.) degrees in electrical engineering from RWTH Aachen University, Germany, in 2012 and 2018, respectively. Until the end of 2020, he was the Head of the Medical Signal Processing Group at the Chair for Medical Information Technology, RWTH Aachen. Since then, he is an Assistant Professor (tenure track) and the Head of KIS*MED (AI Systems in Medicine Laboratory), TU Darmstadt, Germany. His research interests include unobtrusive sensing of vital signs, sensor fusion, and machine learning in medicine.

Scientific area: Technologies / Image-Signal Process / Unobtrusive Sensing
Human Activity Recognition / Deep Learning / Sensors Fusion / Signal Processing