Nifedipine-Induced Changes in the Electrohysterogram of Preterm Contractions: Feasibility in Clinical Practice

Objective. Evaluating changes in the power spectral density (PSD) peak frequency of the electrohysterogram (EHG) caused by nifedipine in women with preterm contractions. Methods. Calculation of the PSD peak frequency in EHG contraction bursts at different times of nifedipine treatment in women in gestational age 24 to 32 weeks with contractions. Results. A significant (P < .05) decrease of PSD peak frequency between EHG signals measured before and 15 minutes after administration of nifedipine. A significant (P < .05) decrease in PSD peak frequency comparing signals recorded within 24 hours after administration of nifedipine to signals 1 day after tocolytic treatment. A higher average PSD peak frequency for patients delivering within 1 week than that for patients delivering after 1 week from nifedipine treatment (P > .05). Conclusions. EHG signal analysis has great potential for quantitative monitoring of uterine contractions. Treatment with nifedipine leads to a shift to lower PSD peak frequency in the EHG signal

Comparison of electrohysterogram signal measured by surface electrodes with different designs: A computational study with dipole band and abdomen models

Non-invasive measurement of uterine activity using electrohysterogram (EHG) surface electrodes has been attempted to monitor uterine contraction. This study aimed to computationally compare the performance of acquiring EHG signals using monopolar electrode and three types of Laplacian concentric ring electrodes (bipolar, quasi-bipolar and tri-polar). With the implementation of dipole band model and abdomen model, the performances of four electrodes in terms of the local sensitivity were quantifed by potential attenuation. Furthermore, the efects of fat and muscle thickness on potential attenuation were evaluated using the bipolar and tri-polar electrodes with diferent radius. The results showed that all the four types of electrodes detected the simulated EHG signals with consistency. That the bipolar and tri-polar electrodes had greater attenuations than the others, and the shorter distance between the origin and location of dipole band at 20dB attenuation, indicating that they had relatively better local sensitivity. In addition, ANOVA analysis showed that, for all the electrodes with diferent outer ring radius, the efects of fat and muscle on potential attenuation were signifcant (all p<0.01). It is therefore concluded that the bipolar and tri-polar electrodes had higher local sensitivity than the others, indicating that they can be applied to detect EHG efectively

Blind source separation for clutter and noise suppression in ultrasound imaging:review for different applications

Blind source separation (BSS) refers to a number of signal processing techniques that decompose a signal into several 'source' signals. In recent years, BSS is increasingly employed for the suppression of clutter and noise in ultrasonic imaging. In particular, its ability to separate sources based on measures of independence rather than their temporal or spatial frequency content makes BSS a powerful filtering tool for data in which the desired and undesired signals overlap in the spectral domain. The purpose of this work was to review the existing BSS methods and their potential in ultrasound imaging. Furthermore, we tested and compared the effectiveness of these techniques in the field of contrast-ultrasound super-resolution, contrast quantification, and speckle tracking. For all applications, this was done in silico, in vitro, and in vivo. We found that the critical step in BSS filtering is the identification of components containing the desired signal and highlighted the value of a priori domain knowledge to define effective criteria for signal component selection

Feasibility and analysis of bipolar concentric recording of Electrohysterogram with flexible active electrode

The conduction velocity and propagation patterns of Electrohysterogram (EHG) provide fundamental information about uterine electrophysiological condition. The accuracy of these measurements can be impaired by both the poor spatial selectivity and sensitivity to the relative direction of the contraction propagation associated with conventional disc electrodes. Concentric ring electrodes could overcome these limitations the aim of this study was to examine the feasibility of picking up surface EHG signals using a new flexible tripolar concentric ring electrode (TCRE), and to compare it with conventional bipolar recordings. Simultaneous recording of conventional bipolar signals and bipolar concentric EHG (BC-EHG) were carried out on 22 pregnant women. Signal bursts were characterized and compared. No significant differences among channels in either duration or dominant frequency in the Fast Wave High frequency range were found. Nonetheless, the high pass filtering effect of the BC-EHG records resulted in lower frequency content within the range 0.1 to 0.2 Hz than the bipolar ones. Although the BC-EHG signal amplitude was about 5-7 times smaller than that of bipolar recordings, similar signal-to-noise ratio was obtained. These results suggest that the flexible TCRE is able to pick up uterine electrical activity and could provide additional information for deducing uterine electrophysiological condition.The authors are grateful to the Obstetrics Unit of the Hospital Universitario La Fe de Valencia (Valencia, Spain), where the recording sessions were carried out. The work was supported in part by the Ministerio de Ciencia y Tecnologia de Espana (TEC2010-16945), by the Universitat Politecnica de Valencia (PAID SP20120490) and Generalitat Valenciana (GV/2014/029) and by General Electric Healthcare.Ye Lin, Y.; Alberola Rubio, J.; Prats Boluda, G.; Perales Marin, AJ.; Desantes, D.; Garcia Casado, FJ. (2015). 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Influence of Electrode Placement on Signal Quality for Ambulatory Pregnancy Monitoring

Noninvasive fetal health monitoring during pregnancy has become increasingly important in order to prevent complications, such as fetal hypoxia and preterm labor. With recent advances in signal processing technology using abdominal electrocardiogram (ECG) recordings, ambulatory fetal monitoring throughout pregnancy is now an important step closer to becoming feasible. The large number of electrodes required in current noise-robust solutions, however, leads to high power consumption and reduced patient comfort. In this paper, requirements for reliable fetal monitoring using a minimal number of electrodes are determined based on simulations and measurement results. To this end, a dipole-based model is proposed to simulate different electrode positions based on standard recordings. Results show a significant influence of bipolar lead orientation on maternal and fetal ECG measurement quality, as well as a significant influence of interelectrode distance for all signals of interest

Prediction of Preterm Deliveries from EHG Signals Using Machine Learning

There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants are most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. In extreme cases, this can also lead to long-term conditions, such as cerebral palsy, mental retardation, learning difficulties, including poor health and growth. In the US alone, the societal and economic cost of preterm births, in 2005, was estimated to be $26.2 billion, per annum. In the UK, this value was close to £2.95 billion, in 2009. Many believe that a better understanding of why preterm births occur, and a strategic focus on prevention, will help to improve the health of children and reduce healthcare costs. At present, most methods of preterm birth prediction are subjective. However, a strong body of evidence suggests the analysis of uterine electrical signals (Electrohysterography), could provide a viable way of diagnosing true labour and predict preterm deliveries. Most Electrohysterography studies focus on true labour detection during the final seven days, before labour. The challenge is to utilise Electrohysterography techniques to predict preterm delivery earlier in the pregnancy. This paper explores this idea further and presents a supervised machine learning approach that classifies term and preterm records, using an open source dataset containing 300 records (38 preterm and 262 term). The synthetic minority oversampling technique is used to oversample the minority preterm class, and cross validation techniques, are used to evaluate the dataset against other similar studies. Our approach shows an improvement on existing studies with 96% sensitivity, 90% specificity, and a 95% area under the curve value with 8% global error using the polynomial classifier

Nrf2-interacting nutrients and COVID-19 : time for research to develop adaptation strategies

There are large between- and within-country variations in COVID-19 death rates. Some very low death rate settings such as Eastern Asia, Central Europe, the Balkans and Africa have a common feature of eating large quantities of fermented foods whose intake is associated with the activation of the Nrf2 (Nuclear factor (erythroid-derived 2)-like 2) anti-oxidant transcription factor. There are many Nrf2-interacting nutrients (berberine, curcumin, epigallocatechin gallate, genistein, quercetin, resveratrol, sulforaphane) that all act similarly to reduce insulin resistance, endothelial damage, lung injury and cytokine storm. They also act on the same mechanisms (mTOR: Mammalian target of rapamycin, PPAR gamma:Peroxisome proliferator-activated receptor, NF kappa B: Nuclear factor kappa B, ERK: Extracellular signal-regulated kinases and eIF2 alpha:Elongation initiation factor 2 alpha). They may as a result be important in mitigating the severity of COVID-19, acting through the endoplasmic reticulum stress or ACE-Angiotensin-II-AT(1)R axis (AT(1)R) pathway. Many Nrf2-interacting nutrients are also interacting with TRPA1 and/or TRPV1. Interestingly, geographical areas with very low COVID-19 mortality are those with the lowest prevalence of obesity (Sub-Saharan Africa and Asia). It is tempting to propose that Nrf2-interacting foods and nutrients can re-balance insulin resistance and have a significant effect on COVID-19 severity. It is therefore possible that the intake of these foods may restore an optimal natural balance for the Nrf2 pathway and may be of interest in the mitigation of COVID-19 severity

Cabbage and fermented vegetables : From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19

Large differences in COVID-19 death rates exist between countries and between regions of the same country. Some very low death rate countries such as Eastern Asia, Central Europe, or the Balkans have a common feature of eating large quantities of fermented foods. Although biases exist when examining ecological studies, fermented vegetables or cabbage have been associated with low death rates in European countries. SARS-CoV-2 binds to its receptor, the angiotensin-converting enzyme 2 (ACE2). As a result of SARS-CoV-2 binding, ACE2 downregulation enhances the angiotensin II receptor type 1 (AT(1)R) axis associated with oxidative stress. This leads to insulin resistance as well as lung and endothelial damage, two severe outcomes of COVID-19. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is the most potent antioxidant in humans and can block in particular the AT(1)R axis. Cabbage contains precursors of sulforaphane, the most active natural activator of Nrf2. Fermented vegetables contain many lactobacilli, which are also potent Nrf2 activators. Three examples are: kimchi in Korea, westernized foods, and the slum paradox. It is proposed that fermented cabbage is a proof-of-concept of dietary manipulations that may enhance Nrf2-associated antioxidant effects, helpful in mitigating COVID-19 severity.Peer reviewe