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.
Prof. Christian Graeff and Prof. Marco Durante