Continuous IoT-based maternal monitoring: system design, evaluation, opportunities, and challenges

Maternal care encompasses health care services for pregnant women during pregnancy, childbirth, and the postpartum period. Maternity care providers aim to ensure a healthy pregnancy, safe delivery, and smooth transition to motherhood. Traditional maternal care is offered through regular check-ups by health care professionals. In recent years, the emergence of Internet-of-Things (IoT)-based systems has transformed the way health care services are provided. These systems offer low-cost ubiquitous monitoring in everyday life settings and can be used for maternal monitoring. However, IoT-based maternal monitoring systems lack a comprehensive approach in maternal care because they are limited by sensing capabilities, specific health problems, and short periods of monitoring. Moreover, the use of IoT-based systems formaternal health monitoring requires addressing critical quality attributes, such as feasibility, energy efficiency, and reliability and validity of the collected physiological parameters. Quality assessment methods also must be integrated with such systems to discard the noisy part of collected parameters and improve the data quality. Furthermore, long-term, continuous IoT-based maternal monitoring by collecting data that was not traditionally available provides new opportunities, including analyzing the trend of physiological parameters during pregnancy and postpartum, as well as detecting maternal health issues. This thesis presents an IoT-based maternal monitoring system and explores its potential in maternal care. We evaluate the system’s feasibility, reliability, and energy efficiency. We also discuss the practical challenges of implementing the system. Then, we validate the heart rate (HR) and heart rate variability (HRV) parameters that the system collects while the user is asleep and awake. In addition, we propose a deep-learning-based method for quality assessment of HR and HRV parameters to discard unreliable data and improve health decisions. We use the system to collect data from 62 pregnant women during pregnancy and three-months postpartum. Then, the reliable HR and HRV parameters are used to track the trends during pregnancy and postpartum. Finally, we investigate maternal loneliness as a major mental health problem. We develop two predictive models to detect maternal loneliness during late pregnancy and the postpartum period. The models use the objective health parameters passively collected by the system and achieve high performance (weighted F1 scores > 0.87)

Changes in Heart Rate, Heart Rate Variability, Breathing Rate, and Skin Temperature throughout Pregnancy and the Impact of Emotions—A Longitudinal Evaluation Using a Sensor Bracelet

(1) Background: Basic vital signs change during normal pregnancy as they reflect the adaptation of maternal physiology. Electronic wearables like fitness bracelets have the potential to provide vital signs continuously in the home environment of pregnant women. (2) Methods: We performed a prospective observational study from November 2019 to November 2020 including healthy pregnant women, who recorded their wrist skin temperature, heart rate, heart rate variability, and breathing rate using an electronic wearable. In addition, eight emotions were assessed weekly using five-point Likert scales. Descriptive statistics and a multivariate model were applied to correlate the physiological parameters with maternal emotions. (3) Results: We analyzed data from 23 women using the electronic wearable during pregnancy. We calculated standard curves for each physiological parameter, which partially differed from the literature. We showed a significant association of several emotions like feeling stressed, tired, or happy with the course of physiological parameters. (4) Conclusions: Our data indicate that electronic wearables are helpful for closely observing vital signs in pregnancy and to establish modern curves for the physiological course of these parameters. In addition to physiological adaptation mechanisms and pregnancy disorders, emotions have the potential to influence the course of physiological parameters in pregnancy

Robust Characterization of the Uterine Myoelectrical Activity in Different Obstetric Scenarios

[EN] Electrohysterography (EHG) has been shown to provide relevant information on uterine activity and could be used for predicting preterm labor and identifying other maternal fetal risks. The extraction of high-quality robust features is a key factor in achieving satisfactory prediction systems from EHG. Temporal, spectral, and non-linear EHG parameters have been computed to characterize EHG signals, sometimes obtaining controversial results, especially for non-linear parameters. The goal of this work was to assess the performance of EHG parameters in identifying those robust enough for uterine electrophysiological characterization. EHG signals were picked up in different obstetric scenarios: antepartum, including women who delivered on term, labor, and post-partum. The results revealed that the 10th and 90th percentiles, for parameters with falling and rising trends as labor approaches, respectively, differentiate between these obstetric scenarios better than median analysis window values. Root-mean-square amplitude, spectral decile 3, and spectral moment ratio showed consistent tendencies for the different obstetric scenarios as well as non-linear parameters: Lempel-Ziv, sample entropy, spectral entropy, and SD1/SD2 when computed in the fast wave high bandwidth. These findings would make it possible to extract high quality and robust EHG features to improve computer-aided assessment tools for pregnancy, labor, and postpartum progress and identify maternal fetal risks.This work was supported by the Spanish Ministry of Economy and Competitiveness, the European Regional Development Fund (MCIU/AEI/FEDER, UE RTI2018-094449-A-I00-AR) and the Generalitat Valenciana (AICO/2019/220 & GV/2018/104)Mas-Cabo, J.; Ye Lin, Y.; Garcia-Casado, J.; Díaz-Martínez, MDA.; Perales-Marin, A.; Monfort-Ortiz, R.; Roca-Prats, A.... (2020). Robust Characterization of the Uterine Myoelectrical Activity in Different Obstetric Scenarios. Entropy. 22(7):1-15. https://doi.org/10.3390/e22070743S115227Wagura, P., Wasunna, A., Laving, A., Wamalwa, D., & Ng’ang’a, P. (2018). Prevalence and factors associated with preterm birth at kenyatta national hospital. BMC Pregnancy and Childbirth, 18(1). doi:10.1186/s12884-018-1740-2Liu, L., Johnson, H. 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Cardiovascular Evaluation in Bitches in Oestrus, Pregnancy and Puerperium

Background: Pregnancy may change maternal hemodynamic, which is considered a physiological mechanism for adaptation. Cardiac output tends to be influenced by reductions in vascular resistance and increases in uterine vasculature, as well as reduced autonomic tone combined with gestational physiological anaemia and increased blood volume due to increased plasma volume and hormonal mechanisms. In bitches, few studies have been conducted investigating the changes of the system and the clinical implications for the mother and foetuses due to poor cardiac adaptation during pregnancy.Materials, Methods & Results: Systolic blood pressure (SBP), electrocardiographic and Doppler echocardiographic measurements and serum sodium (Na), potassium (K), calcium (Ca) and phosphorus (P) levels were evaluated in six bitches of reproductive age. An evaluation was performed in oestrus (M0), followed by evaluations at 25 (M1), 45 (M2), and 60 days (M3) after the last natural or artificial insemination and 15 days after delivery (M4). For the statistical analysis, the means, medians and the standard deviation were calculated. The data were analysed using ANOVA and the Tukey test, with significance level of 5%. A descriptive analysis was performed for color Doppler in echocardiogram evaluation, cardiac axis and rhythm in electrocardiogram evaluation. In the electrolytic evaluation, significant differences were found only in the serum levels of Na, noticed as a reduction in M0-M1 and M3-M2 and an increase in M1-M2 and M3-M4. No significant differences were observed in the SBP, although there was a tendency to SBP reduction. ECG parameters were not significantly different, with no rhythm or conduction disturbances. There was not a significant difference in HR. Four animals (66.6%) had axis deviation to the right when comparing the oestrous phase with the final quarter of pregnancy. The echocardiographic parameters did not show significant changes.Discussion: The reduction observed in Na can occur by salt depletion, by dilutional or metabolic mechanisms. In contrast, the elevation in Na concentration could occur as a result of fluid and electrolyte retention by kidneys during gestation. The absence of electrocardiographic changes may be justified by the stability of mean serum potassium concentrations. An increase in HR five days before the expected calving time, demonstrating the maximum cardiac activity in this gestational phase, is related by other authors, therefore, in the present study, the absence of significant change in HR can be explained by the period in which the data collection was performed, 45 days of gestation, being therefore prior to the period of greatest HR. The cardiac axis deviation can be explained by the distension of the gravid uterus that cause compression of the adjacent organs, leading to diaphragmatic compression and consequent repositioning of the thoracic structures. A tendency to SBP reduction observed is directly influenced by peripheral vascular resistance and cardiac output that occur during pregnancy. Although the echocardiographic findings did not show changes, it is suggested that there are changes related to increased blood volume in pregnancy to provide an appropriate blood flow to the conceptus. It was concluded that pregnancy and the postpartum period in bitches did not cause changes in electrolytes levels, SBP values, echocardiographic and electrocardiographic parameters as compared to values obtained during oestrus