NDLI: Myometrium electromechanical modeling for internal uterine pressure estimation by electrohysterography

Content Provider	IEEE Xplore Digital Library
Author	Rabotti, C. Mischi, M. van Laar, J.O.E.H. Oei, S.G. Bergmans, J.W.M.
Copyright Year	2009
Description	Author affiliation: Department of Obstetrics and Gynecology, Ma¿xima Medical Center, Veldhoven, the Netherlands. Contact (van Laar, J.O.E.H.; Oei, S.G.) \|\| Faculty of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (Rabotti, C.; Mischi, M.; Bergmans, J.W.M.)
Abstract	During delivery, quantitative information on the uterine activity can be provided by internal uterine pressure (IUP) recordings using an invasive intrauterine pressure catheter (IUPC). The electrohysterogram, which measures the electrical signal that drives the mechanical contraction of the uterine muscle and the consequent IUP increase, is recorded by electrodes placed on the abdomen. Recent work demonstrated the possibility of reliably estimating the IUP noninvasively by electrohysterographic (EHG) signal analysis. To further improve the accuracy of IUP estimates, we investigated the use of three nonlinear functions for modeling the relationship between the electrical activation measured by the EHG signal and the mechanical response of the uterine muscle. The feature employed for obtaining a first estimate of the IUP is the unnormalized first statistical moment of the EHG spectrum. The relationship between the extracted feature and the IUP is modeled by a second-order polynomial, a logarithmic, and an exponential function. For validation, the IUPC and the EHG signals were recorded on nine women in labor. A second-order polynomial model already provided estimates that are highly correlated with the IUPC signal (r = 3D 0.73). However, the logarithmic model resulted to be the most accurate, especially in terms of root mean squared error (RMSE = 3D 5.13 mmHg).
Starting Page	6259
Ending Page	6262
File Size	480303
Page Count	4
File Format	PDF
ISBN	9781424432967
ISSN	1557170X
DOI	10.1109/IEMBS.2009.5332397
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Polynomials Mechanical variables measurement Electric variables measurement Frequency estimation Muscles Signal analysis Catheters Electrodes Abdomen Feature extraction
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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