Research Article
Real‐time signal processing by adaptive repeated median filters
Abstract
In intensive care, a basic goal is to extract the signals from very noisy time series in real time. We propose a robust online filter with an adaptive window width, which yields a smooth representation of the denoised data in stable periods and which is also able to trace typical patterns such as level shifts or trend changes with small time delay. Several versions of this method are evaluated and compared with a simulation study and on real data. Copyright © 2009 John Wiley & Sons, Ltd.
Citing Literature
Number of times cited according to CrossRef: 7
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- Viktoria Zettel, Muhammad Haseeb Ahmad, Annika Hitzemann, Marius Nache, Olivier Paquet‐Durand, Thomas Schöck, Florian Hecker, Bernd Hitzmann, Optische Prozessanalysatoren für die Lebensmittelindustrie, Chemie Ingenieur Technik, 10.1002/cite.201500097, 88, 6, (735-745), (2016).
- M. Borowski, S. Siebig, C. Wrede, M. Imhoff, Reducing False Alarms of Intensive Care Online-Monitoring Systems: An Evaluation of Two Signal Extraction Algorithms, Computational and Mathematical Methods in Medicine, 10.1155/2011/143480, 2011, (1-11), (2011).
- Suzanne Lesecq, Sylvie Charbonnier, Signal processing for monitoring and diagnosis: Medical applications, International Journal of Adaptive Control and Signal Processing, 10.1002/acs.1150, 24, 5, (343-345), (2010).
- M. Borowski, M. Imhoff, K. Schettlinger, U. Gather, Robust and Adaptive Filtering of Multivariate Online-Monitoring Time Series, 4th European Conference of the International Federation for Medical and Biological Engineering, 10.1007/978-3-540-89208-3_42, (167-170), (2009).
