Resource type
Publication year

Automatic Cardiotocography Diagnostic System Based on Hilbert Transform and Adaptive Threshold Technique

Resource type
Authors/contributors
Title
Automatic Cardiotocography Diagnostic System Based on Hilbert Transform and Adaptive Threshold Technique
Abstract
The visual analysis of cardiotocographic examinations is a very subjective process. The accurate detection and segmentation of the fetal heart rate (FHR) features and their correlation with the uterine contractions in time allow a better diagnostic and the possibility of anticipation of many problems related to fetal distress. This paper presents a computerized diagnostic aid system based on digital signal processing techniques to detect and segment changes in the FHR and the uterine tone signals automatically. After a pre-processing phase, the FHR baseline detection is calculated. An auxiliary signal called detection line is proposed to support the detection and segmentation processes. Then, the Hilbert transform is used with an adaptive threshold for identifying fiducial points on the fetal and maternal signals. For an antepartum (before labor) database, the positive predictivity value (PPV) is 96.80% for the FHR decelerations, and 96.18% for the FHR accelerations. For an intrapartum (during labor) database, the PPV found was 91.31% for the uterine contractions, 94.01% for the FHR decelerations, and 100% for the FHR accelerations. For the whole set of exams, PPV and SE were both 100% for the identification of FHR DIP II and prolonged decelerations.
Publication
IEEE Access
Volume
7
Pages
73085-73094
Date
2019
DOI
10.1109/ACCESS.2018.2877933
ISSN
2169-3536
Library Catalog
IEEE Xplore
Extra
13 citations (Crossref) [2022-09-21] Conference Name: IEEE Access
Citation
Marques, J. A. L., Cortez, P. C., Madeiro, J. P. D. V., Fong, S. J., Schlindwein, F. S., & Albuquerque, V. H. C. D. (2019). Automatic Cardiotocography Diagnostic System Based on Hilbert Transform and Adaptive Threshold Technique. IEEE Access, 7, 73085–73094. https://doi.org/10.1109/ACCESS.2018.2877933