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Automatic Cardiotocography Diagnostic System Based on Hilbert Transform and Adaptive Threshold Technique
JOÃO ALEXANDRE LOBO MARQUES1; PAULO CÉSAR CORTEZ2; JOÃO PAULO DO VALE MADEIRO3; SIMON JAMES FONG4; FERNANDO SOARES SCHLINDWEIN5; VICTOR HUGO C. DE ALBUQUERQUE6
2019-04-09
Source PublicationIEEE Access
ISSN2169-3536
Volume7Pages:73085-73094
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.

KeywordCardiotocography (Ctg) Fetal Heart Rate (Fhr) Hilbert Transform Uterine Contractions (Uc)
DOI10.1109/ACCESS.2018.2877933
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000472204400001
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Scopus ID2-s2.0-85067665369
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorJOÃO ALEXANDRE LOBO MARQUES
Affiliation1.Laboratory of Neuroeconomics,School of Business,University of Saint Joseph,Macau,0000,China
2.Department of Engineering of Teleinformatics,Federal University of Ceará,Fortaleza,60455-900,Brazil
3.Instituto de Engenharias e Desenvolvimento Sustentável,UNILAB,Redenção,62790-000,Brazil
4.Computer and Information Science Department,University of Macau,Macau,0000,China
5.Engineering Department,University of Leicester,Leicester,LE1 7RH,United Kingdom
6.Laboratory of Bioinformatics,University of Fortaleza,Fortaleza,60811-905,Brazil
Recommended Citation
GB/T 7714
JOÃO ALEXANDRE LOBO MARQUES,PAULO CÉSAR CORTEZ,JOÃO PAULO DO VALE MADEIRO,et al. Automatic Cardiotocography Diagnostic System Based on Hilbert Transform and Adaptive Threshold Technique[J]. IEEE Access, 2019, 7, 73085-73094.
APA JOÃO ALEXANDRE LOBO MARQUES., PAULO CÉSAR CORTEZ., JOÃO PAULO DO VALE MADEIRO., SIMON JAMES FONG., FERNANDO SOARES SCHLINDWEIN., & VICTOR HUGO C. DE ALBUQUERQUE (2019). Automatic Cardiotocography Diagnostic System Based on Hilbert Transform and Adaptive Threshold Technique. IEEE Access, 7, 73085-73094.
MLA JOÃO ALEXANDRE LOBO MARQUES,et al."Automatic Cardiotocography Diagnostic System Based on Hilbert Transform and Adaptive Threshold Technique".IEEE Access 7(2019):73085-73094.
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