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Type: Artigo de Periódico
Title: Automatic cardiotocography diagnostic system based on hilbert transform and adaptive threshold technique
Authors: Marques, João Alexandre Lôbo
Cortez, Paulo César
Madeiro, João Paulo do Vale
Fong, Simon James
Schlindwein, Fernando Soares
Albuquerque, Victor Hugo Costa de
Keywords: Fetal heart rate (FHR);Hilbert transform;Uterine contractions (UC);Cardiotocografia;Frequência cardíaca fetal;Cardiotocography (CTG);Transformada de Hilbert;Contração uterina
Issue Date: 2019
Publisher: IEEE Acess
Citation: CORTEZ, P. C. et al. Automatic cardiotocography diagnostic system based on hilbert transform and adaptive threshold technique. IEEE Acess, vol. 7, p. 73085-73094, 2019. DOI: 10.1109/ACCESS.2018.2877933
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.
ISSN: 2169-3536
Appears in Collections:DETE - Artigos publicados em revista científica

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