2021
Konstantinos Nikolaidis, Stein Kristiansen, Thomas Plagemann, Vera Goebel, Knut Liestøl, Mohan Kankanhalli, Gunn Marit Traaen, Britt Overland, Harriet Akre, Lars Aakerøy, Sigurd Steinshamn: "Learning Realistic Patterns from Visually Unrealistic Stimuli: Generalization and Data Anonymization", Journal of Artificial Intelligence Research, Vol 72, 2021, DOI: https://doi.org/10.1613/jair.1.13252
Nikolaidis, Konstantinos; Plagemann, Thomas Peter; Kristiansen, Stein; Goebel, Vera Hermine & Kankanhalli, Mohan (2021). Using Under-Trained Deep Ensembles to Learn Under Extreme Label Noise: A Case Study for Sleep Apnea Detection. IEEE Access. ISSN 2169-3536. 9
Kristiansen, Stein; Hamborg Andersen, Morten; Goebel, Vera Hermine; Plagemann, Thomas Peter; Traaen, Gunn Marit; Øverland, Britt; Akre, Harriet & Gullestad, Lars (2021).Evaluating a Low-Cost Strain Gauge Breathing Sensor for Sleep Apnea Detection at Home.I Gedeon, Ibrahim (Red.), 2021 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE. ISSN 978-1-7281-9441-7. doi: 10.1109/ICCWorkshops50388.2021.9473597
Kristiansen, Stein; Nikolaidis, Konstantinos; Plagemann, Thomas Peter; Goebel, Vera Hermine; Traaen, Gunn Marit; Øverland, Britt; Aakerøy, Lars; Hunt, Tove-Elizabeth; Loennechen, Jan Pål; Steinshamn, Sigurd Loe; Benz, Christina Holt; Anfinsen, Ole Gunnar; Gullestad, Lars & Akre, Harriet (2021). Machine Learning for Sleep Apnea Detection with Unattended Sleep Monitoring at Home. ACM Transactions on Computing for Healthcare (HEALTH). ISSN 2691-1957. 2(2). doi: 10.1145/3433987.
2020
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). https://doi.org/10.1007/s12652-020-02136-2
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, https://doi.org/10.1111/jsr.13036
2019
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)
2018
Stein Kristiansen, Thomas Peter Plagemann, Vera Goebel: An Activity Rule Based Approach to Simulate ADL Sequences. IEEE Access 6: 12551-12572(2018)
Stein Kristiansen, Mari Sonsteby Hugaas, Vera Goebel, Thomas Plagemann, Konstantinos Nikolaidis, Knut Liestøl: Data Mining for Patient Friendly Apnea Detection. IEEE Access 6: 74598-74615 (2018)
Fredrik Løberg, Vera Goebel, 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
2017
Stein Kristiansen, Thomas Plagemann, Vera Goebel: Smooth and crispy: integrating continuous event proximity calculation and discrete event detection. DEBS 2016: 153-160