TY - JOUR TI - Automatic Cardiotocography Diagnostic System Based on Hilbert Transform and Adaptive Threshold Technique AU - Marques, J. A. Lobo AU - Cortez, P. C. AU - Madeiro, J. P. D. V. AU - Fong, S. J. AU - Schlindwein, F. S. AU - Albuquerque, V. H. C. D. T2 - IEEE Access AB - 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. DA - 2019/// PY - 2019 DO - 10.1109/ACCESS.2018.2877933 DP - IEEE Xplore VL - 7 SP - 73085 EP - 73094 SN - 2169-3536 UR - https://ieeexplore.ieee.org/abstract/document/8682138 KW - Acceleration KW - Biomedical monitoring KW - Cardiography KW - Cardiotocography (CTG) KW - Databases KW - FHR DIP II KW - FHR accelerations KW - FHR baseline detection KW - FHR decelerations KW - Fetal heart rate KW - Hilbert transform KW - Hilbert transforms KW - Monitoring KW - PPV KW - Transforms KW - accurate fetal heart rate feature detection KW - accurate fetal heart rate feature segmentation KW - adaptive threshold technique KW - antepartum database KW - automatic cardiotocography diagnostic system KW - auxiliary signal KW - cardiotocographic examinations KW - computerized diagnostic aid system KW - digital signal processing techniques KW - fetal distress KW - fetal heart rate (FHR) KW - fetal signals KW - maternal signals KW - medical signal detection KW - medical signal processing KW - obstetrics KW - patient monitoring KW - positive predictivity value KW - preprocessing phase KW - segmentation processes KW - uterine contractions KW - uterine contractions (UC) KW - uterine tone signals KW - visual analysis ER - TY - JOUR TI - A Heart Rate Variability-based Smart Approach to Analyze Frailty in Older Adults AU - Paulo do Vale Madeiro, João AU - César Cortez, Arnaldo Aires Peixoto Júnior, Paulo AU - Alexandre Lôbo Marques, João AU - Alisson Pessoa Guimarães, Antônio AU - Hebert da Silva Felix, John T2 - The Smart Computing Review AB - This paper presents an algorithm that applies metrics derived from automatic QRS detection and segmentation in electrocardiogram signals for analyzing Heart Rate Variability to study the evolution of metrics in the frequency domain of a clinical procedure. The analysis was performed on three sets of elderly people, who are categorized according to frailty phenotype. The first set was comprised of frail elderly, the second pre-frail elderly, and the third robust elderly. Investigators from many disciplines have been encouraged to contribute to the understanding of molecular and physiological changes in multiple systems that may increase the vulnerability of frail elderly. In this work, the frailty phenotype can be characterized by unintentional weight loss, as self-reported, fatigue assessed by self-report, grip strength (measured directly), physical activity level assessed by self-report and gait speed (measured). The results obtained demonstrate the existence of significant differences between Heart Rate Variability metrics for the three groups, especially considering a higher preponderance for sympathetic nervous system for the group of robust patients in response to postural maneuver. DA - 2015/08/31/ PY - 2015 DO - 10.6029/smartcr.2015.04.002 DP - DOI.org (Crossref) J2 - SmartCR SN - 22344624 UR - http://smartcr.org/view/download.php?filename=smartcr_vol5no4p002.pdf Y2 - 2023/03/22/06:36:15 ER -