Arne Küderle, M. Sc.
Long-term monitoring of physiological parameters is the future of digital health. For patients and doctors, it can provide more meaningful data for diagnosis and to objectively track the effectiveness of interventions. For you and me, unobtrusive long-term monitoring aids the early detection of diseases and disorders and provides us objective feedback to design a lifestyle that supports our health and longevity.
To reach this future, we need two things: (1) Accurate sensors and algorithms that can measure our biosignals even in the chaos our life tends to be from time to time and (2) the ability and the right to view, control, and own the data these sensors produce. I am interested in both challenges. Therefore, I am trying to build the most accurate IMU based algorithms for unobtrusive human movement tracking and I am involved in research and concept development for next-generation systems for medical data handling that are from key importance to enable patient-centered healthcare applications.
Because all research is just wasted workhours if it can not be reproduced and used in final applications, I am a heavy advocate of open-source software and I am working towards building robust, standardised, and easy-to-use software tools that enable other researchers to actual use all the algorithms I and my colleagues develop.
|Since 03/2018||Researcher and Ph.D. student
Machine Learning and Data Analytics Lab,
Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
|10/2015 – 1/2018||M.Sc. in Biomedical Engineering
RWTH Aachen University
Master Thesis: “Development of a wireless Unit for longterm Monitoring of the Knee Joint Kinematics in Arthrosis Patients“
|03/2014 – 05/2015||Research Assistant
Institute of Biophysics, Goethe University Frankfurt
|10/2011 – 11/2014||
B.Sc. in Biophysics
Bachelor Thesis: “IR-Spectroscopy on human skin in vivo using Photothermal, Photoacoustic and Reflectrometry methods“
- Springorium Commemorative Coin (RWTH Aachen University) – 9/2018
- Friedrich-Wilhelm Award (RWTH Aachen University) – 11/2019
- 3rd place ZD.B-Science Slam on the topic of “Medical Data – The Good, the Bad, and the Ugly”