PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Real-Time Fetal Heart Monitoring in Biomagnetic Measurements Using Adaptive Real-Time ICA
S. Waldert, M. Bensch, M. Bogdan, W. Rosenstiel, B. Schölkopf, C.L. Lowery, H. Eswaran and H. Preissl
IEEE Transactions on Biomedical Engineering Volume 54, Number 10, pp. 1867-1874, 2007.

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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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:4024
Deposited By:Bernhard Schölkopf
Deposited On:25 February 2008