A deep learning mixed-data type approach for the classification of FHR signals.

The Cardiotocography (CTG) is a widely diffused monitoring practice, used in Ob-Gyn Clinic to assess the fetal well-being through the analysis of the Fetal Heart Rate (FHR) and the Uterine contraction signals. Due to the complex dynamics regulating the Fetal Heart Rate, a reliable visual interpretation of the signal is almost impossible and results in significant subjective inter and intra-observer variability. Also, the introduction of few parameters obtained from computer analysis did not solve the problem of a robust antenatal diagnosis.

An integrated approach based on advanced CTG parameters and Doppler measurements for late growth restriction management.

Background: The clinical diagnosis of late Fetal Growth Restriction (FGR) involves the integration of Doppler ultrasound data and Fetal Heart Rate (FHR) monitoring through computer assisted computerized cardiotocography (cCTG). The aim of the study was to evaluate the diagnostic power of combined Doppler and cCTG parameters by contrasting late FGR -and healthy controls.

Methods: The study was conducted from January 2018 to May 2020.

Placental dysfunction in uncomplicated and complicated intrauterine growth restriction by preeclampsia and neonatal outcome.

Objectives: To investigate the use of computerized cardiotocography (cCTG) parameters in Intrauterine Growth Restriction (IUGR) pregnancies for the prediction of 1) complication with preeclampsia; 2) placental histological abnormalities, and 3) neonatal outcomes. .

Study Design: A single-center observational retrospective case-control study was performed by reviewing medical records, cCTG databases and pathological reports of women with singleton pregnancy and IUGR uncomplicated (controls) and complicated by preeclampsia (cases).

Impact of nuchal cord on antenatal and intrapartum foetal heart rate surveillance and perinatal outcome.

Analysing antepartum and intrapartum computerised cardiotocographic (cCTG) parameters in physiological term pregnancies with nuchal (NC) or body cord (BC), in order to correlate them with labour events and neonatal outcome. We enrolled 808 pregnant women, composed of 264 with 'one NC', 121 with 'multiple NCs', 39 with BC and 384 with 'no NC', were monitored from the 37th week of gestation before labour, while 49 pregnant women with 'one or more NCs' and 47 with 'no NCs' were analysed during labour. No differences in maternal characteristics, foetal pH at birth and 5-min Apgar score were observed.

Intrapartum cardiotocography with and without computer analysis: a systematic review and meta-analysis of randomized controlled trials.

To evaluate whether intrapartum cardiotocography with computer analysis decreases the incidence of newborn metabolic acidosis or obstetric intervention when compared with visual analysis through a systematic review with meta-analysis of randomized controlled trials. The research was conducted using Medline, Embase, Web of Science, Scopus, ClinicalTrial.gov, Ovid and Cochrane Library as electronic databases from the inception of each database to May 2018.

Ethnic analogies and differences in fetal heart rate variability signal: A retrospective study.

Aim: We aimed to analyze computerized cardiotocographic (cCTG) parameters (including fetal heart rate baseline, short-term variability, Delta, long-term irregularity [LTI], interval index [II], low frequency [LF], movement frequency [MF], high frequency [HF], and approximate entropy [ApEn]) in physiological term pregnancies in order to correlate them with ethnic differences. The clinical meaning of numerical parameters may explain physiological or paraphysiological phenomena that occur in fetuses of different ethnic origins.

Methods: A total of 696 pregnant women, including 384 from Europe, 246 from sub-Saharan Africa, 45 from South-East Asia, and 21 from South America, were monitored from the 37th to the 41st week of gestation.

Computerised analysis of antepartum foetal heart parameters: New reference ranges.

We selected 4012 cCTG records (one trace for each patient) performed in healthy pregnancies from 30th to 42nd gestational week using foetal heart rate (FHR), short-term variability (STV), long-term irregularity (LTI), Delta, approximate entropy (ApEn), spectral components as low frequency (LF), median frequency (MF), high frequency (HF) and LF/(HF + MF) ratio were analysed. Reference nomograms were created and sensitivity and specificity for the prediction of foetal compromise were calculated which were 90% and 89%, respectively. Changes of cCTG parameters according to gestational week were evaluated: FHR (r = -.

Telemedicine to Improve Access to Specialist Care in Fetal Heart Rate Monitoring: Analysis of 17 Years of TOCOMAT Network Clinical Activity.

Background: The objective of this article is to provide an overview of the clinical experience of our telemedicine network (TOCOMAT) for fetal well-being assessment through computerized Cardiotocography (cCTG), analyzing cultural, socioeconomic, and environmental conditions of pregnant women and its economic sustainability over time.

Materials And Methods: We used the central data store, including all cCTG records collected in Campania region (Italy) during 17 years of activity. The Operations Center acquires the traces recorded in the Remote Units and simultaneously performs a complex fetal heart rate analysis.

Evaluation of the Acceleration and Deceleration Phase-Rectified Slope to Detect and Improve IUGR Clinical Management.

Objective: This study used a new method called Acceleration (or Deceleration) Phase-Rectified Slope, APRS (or DPRS) to analyze computerized Cardiotocographic (cCTG) traces in intrauterine growth restriction (IUGR), in order to calculate acceleration- and deceleration-related fluctuations of the fetal heart rate, and to enhance the prediction of neonatal outcome.

Method: Cardiotocograms from a population of 59 healthy and 61 IUGR fetuses from the 30th gestation week matched for gestational age were included. APRS and DPRS analysis was compared to the standard linear and nonlinear cCTG parameters.

Blood pressure variability and cardiovascular autonomic control during hemodialysis in peripheral vascular disease patients.

Hemodialysis (HD) patients with peripheral vascular disease (PVD) are at higher risk of mortality. The main objectives of this work were to investigate the hypothesis of an association between the PVD and an altered control system on peripheral resistance in response to volume depletion induced by HD treatment; and to investigate whether HD induced increase of pulse pressure (PP) is associated with PVD. Continuous blood pressure (BP) was recorded during HD treatment at the beginning and at the end of HD.

Effects of dialysate glucose concentration on heart rate variability in chronic hemodialysis patients: results of a prospective randomized trial.

Background: Chronic hemodialysis (HD) patients suffer from an appallingly high cardiovascular mortality. During HD, patients are exposed to dialysate glucose, which may alter blood glucose levels and thus exert effects on the autonomic nervous system. Heart rate variability (HRV) is an established indicator of autonomic nervous system activity and a predictor of cardiovascular outcomes.

Multifractality and heart rate variability.

In this paper, we participate to the discussion set forth by the editor of Chaos for the controversy, "Is the normal heart rate chaotic?" Our objective was to debate the question, "Is there some more appropriate term to characterize the heart rate variability (HRV) fluctuations?" We focused on the approximately 24 h RR series prepared for this topic and tried to verify with two different techniques, generalized structure functions and wavelet transform modulus maxima, if they might be described as being multifractal. For normal and congestive heart failure subjects, the h(q) exponents showed to be decreasing for increasing q with both methods, as it should be for multifractal signals. We then built 40 surrogate series to further verify such hypothesis.

The estimation of long-term memory characteristics in MEA neuronal culture recordings.

The nonlinear analysis of multichannel MEA recordings from neuronal networks is becoming a central topic in Neuroengineering. Up-to-date these kind of analyses required complex ad hoc methods. In this paper we introduce a new approach that allows the analysis of the whole-neuronal-network-activity with well-established nonlinear signal processing methods.

A blind method for the estimation of the Hurst exponent in time series: theory and application.

Nowadays many methods for the estimation of self-similarity (Hurst coefficient, H) in time series are available. Most of them, even if very effective, need some a priori information to be applied. We analyzed the eight most used methods for H estimation (working both in time and in frequency).

How do TTX and AP5 affect the post-recovery neuronal network activity synchronization?

A lot of methods were created in last decade for the spatio-temporal analysis of multi-electrode array (MEA) neuronal data sets. The greater part of these methods does not consider the network as a whole but performs an analysis channel by channel. In this paper we illustrate how a very simple approach that considers the total network activity, is able to show interesting neuronal network features.

Assessing nonlinear properties of heart rate variability from short-term recordings: are these measurements reliable?

Several parameters assessing nonlinear properties of heart rate variability (HRV) from short-term (<10 min) laboratory recordings have been proposed so far, but their reliability is unknown. In this study, we addressed this issue analysing a comprehensive set of these indices. In 42 healthy subjects (mean age (min-max): 38 (26-56) years, 21 men) we recorded 5 min of supine ECG in two consecutive days.

Long-term invariant parameters obtained from 24-h Holter recordings: a comparison between different analysis techniques.

Over the last two decades, a large number of different methods had been used to study the fractal-like behavior of the heart rate variability (HRV). In this paper some of the most used techniques were reviewed. In particular, the focus is set on those methods which characterize the long memory behavior of time series (in particular, periodogram, detrended fluctuation analysis, rescale range analysis, scaled window variance, Higuchi dimension, wavelet-transform modulus maxima, and generalized structure functions).

Nonlinear indices of heart rate variability in chronic heart failure patients: redundancy and comparative clinical value.

Aims: We aimed to assess the mutual interrelationships and to compare the prognostic value of a comprehensive set of nonlinear indices of heart rate variability (HRV) in a population of chronic heart failure (CHF) patients.

Methods And Results: Twenty nonlinear HRV indices, representative of symbolic dynamics, entropy, fractality-multifractality, predictability, empirical mode decomposition, and Poincaré plot families, were computed from 24-hour Holter recordings in 200 stable CHF patients in sinus rhythm (median age [interquartile range]: 54 [47-58] years, LVEF: 23 [19-28]%, NYHA class II-III: 88%). End point for survival analysis (Cox model) was cardiac death or urgent transplantation.

Clinical correlates of non-linear indices of heart rate variability in chronic heart failure patients.

We assessed the clinical correlates of a comprehensive set of non-linear heart rate variability (HRV) indices computed from 24-h Holter recordings for 200 stable chronic heart failure (CHF) patients [median age (lower quartile, upper quartile) 54 (47, 58) years, LVEF 23% (19%, 28%)]. A total of 19 non-linear indices belonging to six major families, namely symbolic dynamics, entropy, empirical mode decomposition, fractality-multifractality, unpredictability and Poincaré plots, were considered. Most indices showed a significant association with ejection fraction and with the severity of symptoms, while only two (one each from the fractality and Poincaré plot families) showed an association with aetiology.

HRV scaling exponent identifies postinfarction patients who might benefit from prophylactic treatment with amiodarone.

Analysing the Holter recordings collected at baseline during the European Myocardial Infarction Amiodarone Trial (EMIAT), we evaluate the possibility of using alpha, the slope of the power spectrum of heart rate variability signals (HRV) in the vicinity of f = 0, for postinfarction risk stratification. We found no relevant difference in the values of alpha for the placebo population. On the contrary, in the amiodarone arm, the distinction in the survival rates of those with high or low alpha-values was highly significant.

Biomedical signal processing and modeling in cardiovascular systems.

This article revisits the subject of short-term heart-rate and arterial-pressure variability from the perspective of model structures that can be useful in defining signal processing algorithms. We draw a general scheme of the oscillation sources and interactions that contribute to cardiovascular control mechanisms and highlight the elements that were considered in different modeling works. The origin, superposition, and interaction of respiratory high-frequency (HF) and vasomotor low-frequency (LF) rhythms is presented as the integration of supraspinal and spinal circuits, vasomotor activity, and pressure control loops.