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  Real-Time Fetal Heart Monitoring in Biomagnetic Measurements Using Adaptive Real-Time ICA

Waldert, S., Bensch, M., Bogdan, M., Rosenstiel, W., Schölkopf, B., Lowery, C., et al. (2007). Real-Time Fetal Heart Monitoring in Biomagnetic Measurements Using Adaptive Real-Time ICA. IEEE Transactions on Biomedical Engineering, 54(10), 1867-1874. doi:10.1109/TBME.2007.895749.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-CBC1-8 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-10E7-4
Genre: Journal Article

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 Creators:
Waldert, S, Author              
Bensch, M, Author
Bogdan, M, Author
Rosenstiel, W, Author
Schölkopf, B1, 2, Author              
Lowery , CL, Author
Eswaran, H, Author
Preissl, H, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: Electrophysiological signals of the developing fetal brain and heart can be investigated by fetal magnetoencephalography (fMEG). During such investigations, the fetal heart activity and that of the mother should be monitored continuously to provide an important indication of current well-being. Due to physical constraints of an fMEG system, it is not possible to use clinically established heart monitors for this purpose. Considering this constraint, we developed a real-time heart monitoring system for biomagnetic measurements and showed its reliability and applicability in research and for clinical examinations. The developed system consists of real-time access to fMEG data, an algorithm based on Independent Component Analysis (ICA), and a graphical user interface (GUI). The algorithm extracts the current fetal and maternal heart signal from a noisy and artifact-contaminated data stream in real-time and is able to adapt automatically to continuously varying environmental parameters. This algorithm has been na med Adaptive Real-time ICA (ARICA) and is applicable to real-time artifact removal as well as to related blind signal separation problems.

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 Dates: 2007-09
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1109/TBME.2007.895749
BibTex Citekey: 4361
 Degree: -

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Title: IEEE Transactions on Biomedical Engineering
Source Genre: Journal
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Publ. Info: New York, NY : Institute of Electrical and Electronics Engineers
Pages: - Volume / Issue: 54 (10) Sequence Number: - Start / End Page: 1867 - 1874 Identifier: ISSN: 0018-9294
CoNE: https://pure.mpg.de/cone/journals/resource/991042742034490