Prof. Ralf Seepold
HTWG Konstanz University of Applied Sciences, GermanyFrom Signals to Decisions: Explainable AI and Ubiquitous Sensing for the Future of Digital Sleep Health
Abstract:
Advances in wearable sensing, ambient intelligence, and artificial intelligence are transforming how physiological processes can be monitored in everyday environments. Yet the central challenge of digital health is not simply collecting large volumes of data. The real challenge is converting heterogeneous physiological signals into reliable, interpretable, and clinically meaningful decisions. This keynote explores how explainable artificial intelligence, together with ubiquitous sensing technologies, can bridge the gap between biomedical signals and actionable health insights. Starting from the foundations of biomedical signal acquisition, the talk examines how physiological data, such as EEG, respiration, and body movement, can be captured using wearable and contactless sensing systems embedded in daily life. Building on this signal layer, machine learning and deep learning methods enable the automatic interpretation of complex physiological patterns. Approaches ranging from classical machine learning models to neural architectures, such as convolutional and recurrent networks, enable analysis of continuous streams of physiological data. A central theme of the keynote is the role of explainability in turning algorithmic outputs into insights that clinicians and patients can understand and trust. Sleep medicine serves as a central application domain throughout the talk. Examples include automated sleep stage analysis, detection of sleep apnea, and digital support for insomnia management. The keynote concludes with a broader perspective on intelligent Ambient Assisted Living environments, where continuous sensing, privacy-aware data processing, and transparent artificial intelligence systems enable personalized healthcare and early intervention in everyday life.
Biography:
Prof. Dr. Ralf E. D. Seepold is Chair for Ubiquitous Computing at HTWG Konstanz University of Applied Sciences in Germany and Director of the Ubiquitous Computing Laboratory and the Interdisciplinary Sleep Laboratory. His research focuses on noninvasive physiological measurement, Medical Internet of Things, sleep medicine, ubiquitous artificial intelligence, and digital health technologies. His work aims to develop intelligent systems that integrate sensing, signal processing, and artificial intelligence to support continuous health monitoring and personalized healthcare in everyday environments. His research lies at the intersection of computer science, biomedical engineering, and digital health. A particular focus is on unobtrusive monitoring and analysis of physiological signals using wearable and ambient-sensing technologies. These approaches are applied to areas such as sleep diagnostics, telemedicine, and Ambient Assisted Living systems, where intelligent sensing and data analysis can support clinical assessment and everyday health management.
He has held academic positions in Germany, Spain, and Russia, including a professorship at Universidad Carlos III de Madrid and a co-opted professorship at the University of Seville, where he contributes to doctoral education and international research collaboration. He is also the founder and coordinator of the international SALUS Network, which focuses on citizen-centered digital health solutions in cross-border regions.
Prof. Seepold is an Associate Editor of IEEE Access and a Senior Member of IEEE. He is also an active member of several international scientific societies, including the European Sleep Research Society, the World Sleep Society, and the German Society for Sleep Research and Sleep Medicine.
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