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Startseite›AI x Bio Seminar: Radar Sensing for Contactless Physiological Monitoring During Sleep
AI x Bio Seminar: Radar Sensing for Contactless Physiological Monitoring During Sleep
Education

AI x Bio Seminar: Radar Sensing for Contactless Physiological Monitoring During Sleep

Mo., 13. Juli
19:00 – 20:30
Amalienstraße 17Kostenlos · Website ansehen
Über die Veranstaltung

[IN-PERSON AI × BIO SEMINAR IN MUNICH]
Join us for an enlightening seminar on "Radar Sensing for Contactless Physiological Monitoring During Sleep" featuring Daniel Krauss, a distinguished researcher at the Institute for Artificial Intelligence in Medicine at LMU Munich.
Daniel specializes in radar-based sensing of vital signs and contactless physiological monitoring using machine learning.

What if we could monitor sleep without any sensors or electrodes? This talk delves into how radar technology can make sleep monitoring unobtrusive by capturing subtle movements related to breathing, heartbeat, and body motion. Using REM sleep behavior disorder as a case study, we will explore how this contactless approach could revolutionize the detection of sleep-related markers for neurodegenerative diseases.

Agenda

🕒 19:00 – 20:00
Seminar presentation followed by Q&A
🕗 20:00 – 20:30
Networking session with food and drinks

About the Speaker

Daniel Krauss earned his M.Sc. in Medical Engineering from FAU Erlangen-Nürnberg, focusing on benchmarking sleep/wake detection algorithms. He is now pursuing his PhD under the guidance of Prof. Björn Eskofier, concentrating on contactless physiological monitoring during sleep.
Since May 2026, Daniel has been part of the Institute for Artificial Intelligence in Medicine at LMU Munich, where he investigates radar-based sensing of vital signs, including cardiac monitoring, respiration analysis, and apnea detection. His work emphasizes the importance of unobtrusive monitoring technologies in disease detection and long-term patient care.

📍 Location: Amalienstraße 17, 80333 München

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Amalienstraße 17

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Details
Datum
Mo., 13. Juli
Uhrzeit
19:00 - 20:30
Ort
Amalienstraße 17
Website ansehen

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