Zgheib, R., Kristiansen, S., Conchon, E., Plagemann, T., Goebel, V., Bastide, R.: "A scalable semantic framework for IoT healthcare applications". Journal of Ambient Intelligent Human Computing (2020).

Kristiansen S, Traaen GM, Øverland B, Plagemann T, Gullestad L, Akre H, Nikolaidis K, Aakerøy L, Hunt E, Loennechen JP, Steinshamn S, Bendz C, Anfinsen OG, Goebel V: "Comparing Manual and Automatic Scoring of Sleep Monitoring Data from Portable Polygraphy", Journal of Sleep Research, May 2020,


Konstantinos Nikolaidis, Stein Kristiansen, Vera Goebel, Thomas Plagemann, Knut Liestøl, Mohan Kankanhalli: “Augmenting Physiological Time Series Data: A Case Study for Sleep Apnea Detection”, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD 2019), Wuerzburg, Germany, September 2019

Konstantinos Nikolaidis, Stein Kristiansen, Vera Goebel, Thomas Plagemann: Learning from Higher-Layer Feature Visualizations, arXiv:1903.02313, (not peer-reviewed yet)


, Thomas Peter Plagemann, : An Activity Rule Based Approach to Simulate ADL Sequences. IEEE Access 6: 12551-12572(2018)

, Thomas Plagemann, : Data Mining for Patient Friendly Apnea Detection. IEEE Access 6: 74598-74615 (2018)

, Thomas Plagemann: Quantifying the Signal Quality of Low-cost Respiratory Effort Sensors for Sleep Apnea Monitoring. HealthMedia@MM 2018: 3-11

Kristiansen, Stein; Goebel, Vera Hermine; Karl, Øyri & Plagemann, Thomas Peter (2018). Event-Based Methodology for Real-Time Data Analysis in Cyber Physical Systems, In Silhavy Radek; Petr Silhavy & Zdenka Prokopova (ed.),  Cybernetics Approaches in Intelligent Systems.  Springer.  ISBN 9783319676180.  pp 184 - 195


, Thomas Plagemann, : Smooth and crispy: integrating continuous event proximity calculation and discrete event detection. DEBS 2016: 153-160


Published Jan. 7, 2019 6:59 PM - Last modified Sep. 22, 2020 12:28 PM