Personal Health System Design & Marker Estimation for Health-Behaviour Guidance

About the Presentation: Starting from the example of (automated) dietary monitoring methods, this lecture highlights the technical development of wearable and implantable systems for automated dietary behavior monitoring and advanced health-behaviour guidance. I will talk about our early attempts in sensor design and monitoring in 2005, including transducers and pattern spotting algorithms for chewing, swallowing, and motion, i.e. ‘intake gesture’ detection. The sensor pattern modelling and personalisation challenge will be discussed and our approaches through domain adaptation methods, context hierarchy modelling, as well as self-taught learning. Subsequently, computational analysis methods that represent food intake as an event process will be discussed, including our context-free grammar model. The translational character of the methods will be discussed. In the second part of the talk, I will present our efforts to develop smart, regular-look eyeglasses with frame-integrated sensors and results on food intake timing analysis from a recent free-living study. It will be shown how the eyeglasses advance the field of automated dietary monitoring and integrate previous approaches, including the assessment of the chewing microstructure, food type categorisation and intake amount estimation. Finally, our endeavour to digitally model, analyse, and co-simulate eyeglasses’ frame mechanics jointly with their electrical sensor function will be discussed. On the example of the eyeglasses, I will present a hierarchical multidomain modelling framework to design on-body sensor systems, where layers of device functions are matched with corresponding body models. Based on the framework design and simulations, initial experience and insight into functional design will be discussed. The talk will conclude with an outlook on the opportunities for future personal health system design and generalisation of our multidomain model framework to other classes of on-body systems.

About the Presenter:  Oliver Amft is the founding director of the Chair of Digital Health at the Friedrich Alexander University Erlangen-Nürnberg (FAU). He received the Dipl.-Ing. (M.Sc.) from Chemnitz Technical University in 1999 and the Dr. sc. ETH (Ph.D.) from ETH Zurich in 2008, both in Electrical Engineering and Information Technology.  Oliver Amft was an assistant professor at TU Eindhoven between 2009 and 2013, tenured since 2011. In 2014, he was appointed full professor and established the Chair of Sensor Technology at University of Passau, Faculty of Computer Science and Mathematics. Since 2017, Oliver Amft is a full professor at FAU Erlangen-Nürnberg, Faculty of Medicine. Oliver is an Editorial Board member of IEEE Pervasive Computing, co-editing the regular Wearable Computing column. He is an associaate editor for several key journals related to mobile and wearable health technology, including the IEEE Journal of Biomedical and Health Informatics (J-BHI), and the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT).