@article{marques_automatic_2019, title = {Automatic {Cardiotocography} {Diagnostic} {System} {Based} on {Hilbert} {Transform} and {Adaptive} {Threshold} {Technique}}, volume = {7}, issn = {2169-3536}, url = {https://ieeexplore.ieee.org/abstract/document/8682138}, 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.}, journal = {IEEE Access}, author = {Marques, J. A. Lobo and Cortez, P. C. and Madeiro, J. P. D. V. and Fong, S. J. and Schlindwein, F. S. and Albuquerque, V. H. C. D.}, year = {2019}, note = {13 citations (Crossref) [2022-09-21] Conference Name: IEEE Access}, keywords = {Acceleration, Biomedical monitoring, Cardiography, Cardiotocography (CTG), Databases, FHR DIP II, FHR accelerations, FHR baseline detection, FHR decelerations, Fetal heart rate, Hilbert transform, Hilbert transforms, Monitoring, PPV, Transforms, accurate fetal heart rate feature detection, accurate fetal heart rate feature segmentation, adaptive threshold technique, antepartum database, automatic cardiotocography diagnostic system, auxiliary signal, cardiotocographic examinations, computerized diagnostic aid system, digital signal processing techniques, fetal distress, fetal heart rate (FHR), fetal signals, maternal signals, medical signal detection, medical signal processing, obstetrics, patient monitoring, positive predictivity value, preprocessing phase, segmentation processes, uterine contractions, uterine contractions (UC), uterine tone signals, visual analysis}, pages = {73085--73094}, }