Authors:
A. Herzog
1
;
L. Reicke
1
;
M. Kröger
1
;
C. Sohn
2
and
H. Maul
2
Affiliations:
1
Institute of Dynamics and Vibration Research, Leibniz University Hannover, Germany
;
2
Obstetrics and Gynecology, University Hospital Heidelberg, Germany
Keyword(s):
Uterine, electromyography, pulse detection, stochastic analysis, Karhunen-Loève, principal component.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Medical Image Detection, Acquisition, Analysis and Processing
Abstract:
This contribution presents a new approach for the enhanced analysis of uterine surface electromyography (EMG). First, a pulse detection separates the pulses, which contain the essential information about the uterine contractibility, from the flat line sections during relaxation. The functionality of this semi-automatic algorithm is controlled by two comprehensible parameters. Subsequently, the mean frequency, which serves as a criterion for imminent delivery, is evaluated from the extracted pulses. Although the pulse detection reduces the deviation of the mean frequency significantly, the results are still sensitive to parameter variations in the pulse detection. A stochastic analysis based on the Karhunen-Loe`ve transform (KLT) derives generalised patterns, the eigenforms, from the pulse ensemble. The mean frequency of the first eigenform is less sensitive to parameter variations. Additionally, the correlation between the eigenforms of the left and right surface electrode can serve
as a criterion for the measurement’s quality.
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