Fetal Heart Rate Monitoring Research Articles

Investigation of fetal ECG signal using textile-based electrodes

Fetal heart rate (FHR) monitoring is a technique that can be considered vital tool assisting midwife. This technique is useful in the early recognition of fetal heart defects, stillbirth and prevention of a risky conditions in clinics during pregnancy. The complications due to these threats are currently kept at bay by the extensive use of cardiotocography in clinics. However, cardiotocography suffers from drawbacks such as the need to replace transducer skillfully or the fact that the use of this method is only limited to mother to be staying in clinics. The aim of this article is to present the development of a belt composed of yarns containing different percentages of stainless-steel fibers as conductive yarns. The use of this belt in association with signal processing technique enables the real-time monitoring of FHR by the mother in absence of medical staff. Thus, not only preventing the occurrence of life threatening complexities but also significantly relieving the burden on the social welfare budget. It was concluded that a smart belt containing the highest percentage of stainless-steel fiber offers successful recording of fetal electrocardiogram.

Fetal heart rate monitoring by fusion of estimations from two modalities: A modified Viterbi’s algorithm

Objective:In the context of fetal heart rate (fHR) estimation, the article addresses the fusion of two monomodal estimations into a multimodal one. Electrical and mechanical modalities are considered through the use of abdominal electrocardiogram (ECG) and phonocardiogram (PCG). The aim of the fusion is to provide a fHR estimation, robust against noise sources, and especially against the risk of confusion with the mother heart rate (mHR). Approach:A hidden Markov chain is considered to model variations of the two monomodal fHR estimations and the true fHR. Thanks to the Viterbi’s algorithm (VA), the two fHR estimations are then merged. However, the classical VA does not ensure that the merged estimation always follows the true fHR: it may alternate between the fHR and the mHR, especially when the mother component is not correctly removed from the abdominal ECG. Therefore, a modified VA is proposed to efficiently avoid confusion with mHR. The aim is to discourage large variations between successive states. Results:Comparisons between classical and modified VA are performed on real pregnant women data. The modified VA reduces the confusion between fHR and mHR in major cases compared to the classical VA. For most recordings, the confusion with mHR decreases under 1%, and for the best case, it is reduced from 59% to 0%. Conclusion:The modified VA succeeds to improve the fHR estimation by reducing confusion with mHR. Significance:Fusion of estimations from two modalities is a promising approach for more robust fHR monitoring.

Signal Quality Index for the fetal heart rates: Development and improvements for fetal monitoring

Fetal heart rate (FHR) monitoring is the most widely used tool in clinics to assess fetal health. However, FHR with low-quality signals may somehow exaggerate the risk of the fetus suffering from acidemia, thus contributing to an increase in cesarean section rates. If there is an algorithm capable to identify and reject low-quality signals and then calculate heart rate parameters only on high-quality signals, inappropriate obstetric interventions may be greatly reduced. Currently, only the Signal Quality Index (SQI) is available for adults. When we applied SQI to fetal data, its performance drops dramatically. To fill the gap in the fetal signal quality index, we developed an easy-to-use Fetal heart rate Signal Quality Index (FSQI) in this paper. Firstly, we used a human-in-the-loop strategy to reduce the amount of data annotation effort. Secondly, we developed the FSQI algorithm oriented towards the fetus to identify low-quality signal segments. Further, we proposed a post-processing technique based on fine-grained recognition to identify low-quality signal segments more accurately. Finally, we applied the FSQI algorithm in combination with the existing FHR deceleration event detection algorithm to test the effectiveness of the algorithm. The results showed that the FSQI algorithm we developed achieved an overall accuracy of 99.8842% in signal quality classification, while also eliminating 94.92% of the incorrectly detected deceleration events of current state-of-the-art methods.

Case Report: Peripartum periventricular leukomalacia resulting in cerebral palsy associated with placenta previa in Japan

Intrapartum fetal heart rate monitoring abnormalities had been reported to correlate with decreased umbilical artery base excess associated with neonatal seizures. However, we present an infant born at 35 weeks of gestation diagnosed with cerebral palsy associated with periventricular leukomalacia (PVL) without fetal heart rate (FHR) monitoring abnormalities, According to the summary reports of PVL cases published on the home page of the Japan Obstetric Compensation System for Cerebral Palsy (JOCSC)), the percentage of placenta previa without FHR monitoring abnormalities in the cases of PVL was 5.7% (12/209), which seemed to be higher than the total percentage of placenta previa reported in Japan (0.3-0.5%).

Current Innovative Methods of Fetal pH Monitoring-A Brief Review.

In this study, we explore the "why?", and "how?", monitoring the pH of the fetal scalp is used, and show its limitations. In addition, we review the development of new devices based on the modern physics and nanomaterials serving this topic. Most of the works we found in our search have focused on improving the prognostic of fetal heart rate monitoring, because it is the "golden standard" in determining fetal distress. Although the best-known screening method, it can only provide limited information about the actual status of the fetus. The best predictive assessment, with the highest reproducibility, states that a normal fetal heart rate is indicative of a healthy baby. However, its excellent sensitivity is much reduced when identifying the actual "distress". This is when second-line monitoring methods come into play to guide the diagnostics and direct the obstetrician towards an action plan. Although a historic method, fetal scalp pH sampling is still under review as to its efficiency and place in the current obstetrics. Continuous surveillance of the fetal parameters is important, especially for the fetuses undergoing intrauterine growth restricted (IUGR). Since fetal scalp blood sampling is still under research and is a randomized controlled trial, which compares the relevance of pH and lactates to the obstetrical situation, the maternal-fetal medicine could greatly benefit from the introduction of engineered nanomedicines to the field.

Implementing quality improvement intervention to improve intrapartum fetal heart rate monitoring during COVID-19 pandemic- observational study.

Adherence to intrapartum fetal heart rate monitoring (FHRM) for early decision making in high-risk pregnancies remains a global health challenge. COVID-19 has led to disruption of routine intrapartum care in all income settings. This study aims to evaluate the implementation of quality improvement (QI) intervention to improve intrapartum FHRM and birth outcome before and during pandemic. We conducted an observational study among 10,715 pregnant women in a hospital of Nepal, over 25 months. The hospital implemented QI intervention i.e facilitated plan-do-study-act (PDSA) meetings before and during pandemic. We assessed the change in intrapartum FHRM, timely action in high-risk deliveries and fetal outcomes before and during pandemic. The number of facilitated PDSA meetings increased from an average of one PDSA meeting every 2 months before pandemic to an average of one PDSA meeting per month during the pandemic. Monitoring and documentation of intrapartum FHRM at an interval of less than 30 minutes increased from 47% during pre-pandemic to 73.3% during the pandemic (p<0.0001). The median time interval from admission to abnormal heart rate detection decreased from 160 minutes to 70 minutes during the pandemic (p = 0.020). The median time interval from abnormal FHR detection to the time of delivery increased from 122 minutes to 177 minutes during the pandemic (p = 0.019). There was a rise in abnormal FHR detection during the time of admission (1.8% vs 4.7%; p<0.001) and NICU admissions (2.9% vs 6.5%; p<0.0001) during the pandemic. Despite implementation of QI intervention during the pandemic, the constrains in human resource to manage high risk women has led to poorer neonatal outcome. Increasing human resources to manage high risk women will be key to timely action among high-risk women and prevent stillbirth.

Experiences with intrapartum fetal monitoring in the Netherlands: A survey study

IntroductionWorldwide, cardiotocography is used for continuous monitoring of fetal heart rate (FHR) and uterine contractions during labour. Different methods for FHR registration and registration of contractions are available. Literature about the frequency of use of different fetal monitoring methods is lacking. ObjectiveTo evaluate the use of and preferences for fetal monitoring methods for intrapartum fetal monitoring among Dutch obstetric care providers. Study designBetween October and November 2020 the Dutch Society of Obstetrics and Gynaecology sent an email invitation to all secondary care midwives and gynaecologists (in training) in the Netherlands to complete an online survey regarding the use and personal experience with fetal monitoring methods. The survey mainly consisted of multiple choice questions. Descriptive statistics are reported. Continuous variables were presented as median with interquartile ranges (IQR). Categorical variables were expressed as numbers with percentages. ResultsThe response rate was 29 % (n/N = 510/1748). All Dutch hospitals were represented. The respondents estimated the use of fetal scalp electrode (FSE) at 71 % (IQR 58–85 %) of deliveries. The most common indication for use of the FSE was inadequate external FHR registration (94 %). More than half (54 %) of the respondents reported to use intrauterine pressure catheter with an estimated use of 5 % (IQR 2–8 %) of deliveries. The most common indication for use of intrauterine pressure catheter was inadequate external contraction registration (75 %). The use of ST-analysis was reported in 25 % of the respondents with an estimated use of 60 % (IQR 30–72 %) of deliveries. Almost all respondents (99 %) reported to use fetal blood sampling with an estimated use of 15 % (IQR 10–23 %) of deliveries. Ninety percent of respondents would prefer a valid and reliable external monitoring technique during labour. Thirty-one percent of respondents assume that external fetal monitoring with non-invasive fetal electrocardiography and electrohysterography will become standard care within the next 5 years. ConclusionsCurrently, the FSE is the most used technique for FHR monitoring during labour in the Netherlands. The most common indication for use of FSE is inadequate external FHR registration. Obstetric care providers would prefer a non-invasive external registration method that provides reliable data.

Umbilical Cord Haematoma and Uterine Torsion: Rare Pregnancy Complications at Tu Du Hospital in Vietnam and a Review of Literature

Umbilical cord haematoma (UCH) and uterine torsion are extremely rare complications in pregnancy. These abnormalities may present in acute and spontaneous conditions, however, they should not be neglected in clinical practice when monitoring an abnormal fetal heart without other suspects. The authors hereby report a rare case of UCH and uterine torsion as well as a review of the literature. A female, aged 35 years old (gravida 1, para 0), was admitted to the Emergency Department of Tu Du Hospital, Ho Chi Minh City, Vietnam, due to term gestation without complaints. They had an uncomplicated pregnancy, except a large uterine fibroid and cervical pessary which prevented pre-term birth from 28 weeks of gestational age. A very rare complication of UCH was revealed accidentally following emergency caesarean section associated with abnormal fetal heart rate tracing. Asymptomatic uterine torsion was noticed at the same time as this dramatic event. Pre-operative diagnosis of two rare complications was missed; hence, the authors timely delivered the baby based on another modality of management, computerised cardiotocography. In conclusion, UCH along with uterine torsion is difficult to diagnosis due to its rarity; it is usually an incidental finding. Moreover, no available imaging modality could investigate UCH prior to delivery. Surveillance on fetal heart rate monitoring may be helpful in this fatal situation.

Fetal heartrate tracking system based on intensity of Doppler signal

Doppler-detected fetal heart rate (FHR) tracking is the primary testing method for assessing fetal well-being during antepartum care. However, owing to fetal movements or maternal position variations, the transducer on the abdomen can be displaced, changing the fetal heart location (FHL) and resulting in frequent signal losses and uninterpretable results. In this study, we present FHR monitoring system for continuously maintaining FHR measurements without specifying the location of the Doppler ultrasound transducer. An algorithm is developed to track the FHL based on the intensity of the received Doppler signal. The performance is evaluated by conducting underwater experiments using an object with repeated movements. The tracking error is 7.93° on the X-axis and 1.42° on the Y-axis. Even with those tracking errors, the FHR is continuously recorded. This system can be used to obtain heart rate records without manipulating the position of the transducer and losing the signal.

Fetal growth restriction and stillbirth: Biomarkers for identifying at risk fetuses.

Fetal growth restriction (FGR) is a major cause of stillbirth, prematurity and impaired neurodevelopment. Its etiology is multifactorial, but many cases are related to impaired placental development and dysfunction, with reduced nutrient and oxygen supply. The fetus has a remarkable ability to respond to hypoxic challenges and mounts protective adaptations to match growth to reduced nutrient availability. However, with progressive placental dysfunction, chronic hypoxia may progress to a level where fetus can no longer adapt, or there may be superimposed acute hypoxic events. Improving detection and effective monitoring of progression is critical for the management of complicated pregnancies to balance the risk of worsening fetal oxygen deprivation in utero, against the consequences of iatrogenic preterm birth. Current surveillance modalities include frequent fetal Doppler ultrasound, and fetal heart rate monitoring. However, nearly half of FGR cases are not detected in utero, and conventional surveillance does not prevent a high proportion of stillbirths. We review diagnostic challenges and limitations in current screening and monitoring practices and discuss potential ways to better identify FGR, and, critically, to identify the “tipping point” when a chronically hypoxic fetus is at risk of progressive acidosis and stillbirth.

Implementation of a Revised Classification for Intrapartum Fetal Heart Rate Monitoring and Association to Birth Outcome: A National Cohort Study

(Abstracted from Acta Obstet Gynecol Scand 2022;101:183–192) Electronic fetal monitoring (EFM) is an important tool for detecting fetal hypoxia before the development of adverse neonatal outcomes. Although EFM is highly sensitive, it also has low specificity.

Optimal duration of cardiotocography assessment using the iPREFACE score to predict fetal acidemia

Cardiotocography (CTG) applicability to improve fetal outcomes remains controversial. This study aimed to determine the clinically optimal CTG assessment duration using the integrated score index to predict fetal acidemia by intrapartum fetal heart rate monitoring (iPREFACE score). This single-center, retrospective observational study included 325 normal full-term singleton vaginal deliveries at the Toho University Omori Medical Center, from September 2018 to March 2019. The iPREFACE(10), iPREFACE(30), and iPREFACE(60) scores were calculated at 10, 30, and 60 min immediately before delivery. The primary outcome was fetal acidemia (umbilical artery blood pH < 7.2). The secondary outcome was the correlation between all iPREFACE scores and the umbilical artery blood pH, base excess (BE), and lactate values. Patients without accurate CTG findings or with failure of umbilical artery blood sampling immediately after birth were excluded, leaving 145 patients in the final analysis. Of these, 16, three, and two had umbilical artery blood pH of < 7.2, < 7.1, and < 7.0, respectively. All iPREFACE scores significantly correlated with umbilical artery blood pH, BE, and lactate values. iPREFACE(30) had the highest predictive capacity for fetal acidemia, suggesting that 30 min immediately before delivery may be a useful scoring time in clinical practice.

Maternal and fetal outcomes in meconium-stained amniotic fluid deliveries in a tertiary center

Backgrounds and objectives: Meconium -stained liquor could be an alarming sign of fetal distress and needs continuous fetal heart rate monitoring and urgent interventions. The study aimed to determine maternal and fetal outcomes among women presented with meconium-stained amniotic fluid during labor in relation to mode of delivery, rate of caesarian section, Admission to neonatal intensive care unit and neonatal complications and mortality. Methods: A cross-sectional study was carried out in Duhok Obestetric and Gynecology Teaching Hospital between 1st of September 2019 and 1st of April 2020 where 100 women in labor diagnosed with meconium stained amniotic fluid gestational age between (37_40+6 weeks) included in this study, all participants were meet inclusion criteria for this study and a written consent obtained from them. Results: The study showed that out of 100 participants with meconium stained liquor 48% of them delivered by lower segment cesarean section and the cause of 76.6% of them was fetal distress .The study showed significant statistical association between meconium stained liquor and lower mean scores of APGAR scores at 1 and 5 min , and rate of neonatal intensive care unit admission which was 74 (74.0%) and neonatal complications rate such as meconium Aspiration Syndrome (31.0%), Respiratory Distress Syndrome (14.0%), and Early Neonatal Death (3.0%) ,the study showed that women with spontaneous rupture membrane and thick meconium were significantly more likely to have infants with meconium aspiration syndrome; 46.2% and 48.1% respectively. Conclusions: This study showed that women in labor with meconium-stained amniotic fluid had higher fetal and maternal complications

Abdominal cardiovascular sound recording and analysis using cardio-microphones.

In view of using abdominal microphones for fetal heart rate (FHR) monitoring, the analysis of the obtained abdominal phonocardiogram (PCG) signals is complex due to many interferential noises including blood flow sounds. In order to improve the understanding of abdominal phonocardiography, a preliminary study was conducted in one healthy volunteer and designed to characterize the PCG signals all over the abdomen. Acquisitions of PCG signals in different abdominal areas were realized, synchronously with one thoracic PCG signal and one electrocardiogram signal. The analysis was carried out based on the temporal behavior, amplitude and mean pattern of each signal. The synchronized rhythmic signature of each signal confirms that the PCG signals obtained on the abdominal area are resulting from heart function. However, the abdominal PCG patterns are totally different from the thoracic PCG one, suggesting the recording of vascular blood flow sounds on the abdomen instead of cardiac valve sounds. Moreover, the abdominal signal magnitude depends on the sensor position and therefore to the size of the underlying vessel. The sounds characterization of abdominal PCG signals could help improving the processing of such signals in the purpose of FHR monitoring.

Non-invasive Fetal ECG Signal Quality Assessment based on Unsupervised Learning Approach.

The non-invasive fetal electrocardiogram (FECG) derived from abdominal surface electrodes has been widely used for fetal heart rate (FHR) monitoring to assess fetal well-being. However, the accuracy of FECG-based FHR estimation heavily depends on the quality of FECG signal itself, which can generally be affected by several interference sources such as maternal heart activities and fetal movements. Hence, FECG signal quality assessment (SQA) is an essential task to improve the accuracy of FHR estimation by removing or interpolating low-quality FECG signals. In recent research, various SQA methods based on supervised learning have been proposed. Although these methods could perform accurate SQA, they require large labeled datasets. Nevertheless, the labeled datasets for the FECG SQA are very limited. In this paper, to address this limitation, we propose an unsupervised learning-based SQA method for identifying high and low-quality FECG signal segments. Specifically, a fully convolutional network (FCN)-based autoencoder (AE) is trained for reconstructing a spectrogram derived from FECG. An AE-based feature related to reconstruction error is then calculated to identify high and low-quality FECG segments. In addition, entropy-based features, statistical features, and ECG signal quality indices (SQIs) are also extracted. The high and low-quality segments are identified by feeding the extracted features into self-organizing map (SOM). The experimental results showed that our proposal achieved an accuracy of 98% in high and low-quality signal classification.

Fetal Movement Cancellation in Abdominal Electrocardiogram Recordings Using Signal-to-Signal Translation.

This study addresses the cancellation of fetal movement in abdominal electrocardiogram (AECG) recordings through deep neural networks. For this purpose, a generative signal-to-signal translation model consisting of two coupled generators is employed to discover the relations between fetal movement-contaminated and clean AECG recordings. The model is trained on the fetal ECG synthetic database (FECGSYNDB) which provides AECG recordings from 10 pregnancies along with their ground-truth maternal and fetal ECG signals. The signals are initially segmented into 4-second segments and then fed into the network for denoising. It is demonstrated that the signal-to-signal translation method can reconstruct clean AECG signals with average mean-absolute-error (MAE), root-mean-square deviation (RMSD), and Pearson correlation coefficient (PCC) of 0.099, 0.124, and 99.12% respectively, between clean and denoised AECG signals. Furthermore, the robustness of the method to low signal-to-noise ratio (SNR) input values is shown by an RMSD range of (0.047, 0.352) for SNR values within the range of (-3, 3) dB. Clinical Relevance- The proposed framework allows for the denoising of abdominal ECG signals for non-invasive fetal heart rate monitoring. The approach is accurate due to the use of advanced neural network techniques.

Cardiotocography in Obstetrics: New Solutions for "Routine" Technology.

This work is devoted to the problems of one of the most common screening examinations used in medical practice: fetal cardiotocography (CTG). The technology of ultrasonic monitoring of fetal heart rate (HR) variations has been used for more than 70 years. During this time, it has undergone many upgrades and has been characterized several times as a hopelessly outdated routine technology. Over the past 5–7 years, many in-depth studies and review papers on cardiotocography have appeared, which revealed both the problems and prospects of the technology. Basically, hopes are associated with artificial intelligence, which should increase the accuracy of the analysis of initially inaccurate measurements obtained using ultrasonic testing. At the same time, after the introduction of pulsed operating modes and the appearance of multi-chip sensors, the quality of the original signal remains practically unchanged. This circumstance makes the prospects of the technology very problematic. However, until now, there has not been a reliable replacement for this screening, which is equally safe, non-invasive, and accessible to a wide range of specialists, medical institutions, and patients. The paper discusses and substantiates proposals for improving the technology based on original (different from traditional CTG) methods of processing information received from ultrasonic sensors, which, in the author’s opinion, allow for solving the main problems of CTG: identifying the correct direction of radiation to the fetal heart and to reliably evaluate beat-to-beat heart rate.

An IoMT enabled deep learning framework for automatic detection of fetal QRS: A solution to remote prenatal care

The amalgamation of the Internet of medical things with artificial intelligence shows tremendous benefits in health care. Accurate detection of the fetal QRS complex is highly demanded in fetal heart rate monitoring. Detecting fetal heart rate using electrophysiological signals obtained from abdominal electrodes seems a promising alternative approach. The challenges in determining fetal heart rate from abdominal ECG (AECG) require eliminating maternal components and other noises from the signal at higher accuracy. We propose a novel approach using an IoT-based deep learning architecture to detect fetal QRS complex without eliminating the maternal components in the abdominal ECG. The novelty of the proposed algorithm is twofold: (1) The method uses the time–frequency image (TFI) of abdominal signals as input to the deep neural network and hence promotes the availability of rich features and improves the accurate detection of the fetal QRS complex. (2) The algorithm adapts pre-trained models based on transfer learning for the classification task and thus improves the fetal QRS detection. Two time–frequency approaches, namely Hilbert Huang Transform (HHT) and Stockwell transform (ST), are used to represent input AECG signals as two-dimensional images. The 2013 challenge database is used to evaluate the performance of the proposed approach. The TFI representations of training data using HHT and ST are independently used to train the pre-trained models MobileNet and ResNet18. A comparative analysis is provided in the results between the TFI and deep network architecture. The proposed solution can be suitable for an IoT environment enabling remote fetal monitoring.

Teaching Novice Nurses Fetal Heart Rate Monitoring by Engaging Them in Targeted Digital Content

Excellent programs regarding fetal heart rate (FHR) evaluation exist to educate nurses who care for patients during childbirth. These programs target nurses who have prior experience in the obstetric setting.

Wearable Fetal ECG Monitoring System from Abdominal Electrocardiography Recording.

Fetal electrocardiography (ECG) monitoring during pregnancy can provide crucial information for assessing the fetus’s health status and making timely decisions. This paper proposes a portable ECG monitoring system to record the abdominal ECG (AECG) of the pregnant woman, comprising both maternal ECG (MECG) and fetal ECG (FECG), which could be applied to fetal heart rate (FHR) monitoring at the home setting. The ECG monitoring system is based on data acquisition circuits, data transmission module, and signal analysis platform, which consists of low input-referred noise, high input impedance, and high resolution. The combination of the adaptive dual threshold (ADT) and the independent component analysis (ICA) algorithm is employed to extract the FECG from the AECG signals. To validate the performance of the proposed system, AECG is recorded and analyzed of pregnant women in three different postures (supine, seated, and standing). The result shows that the proposed system can record the AECG in different postures with good signal quality and high accuracy in fetal ECG and heart rate information. Sensitivity (Se), positive predictive accuracy (PPV), accuracy (ACC), and their harmonic mean (F1) are utilized as the metrics to evaluate the performance of the fetal QRS (fQRS) complexes extraction. The average Se, PPV, ACC, and F1 score are 99.62%, 97.90%, 97.40%, and 98.66% for the fQRS complexes extraction,, respectively. This paper shows the proposed system has a promising application in fetal health monitoring.