Fetal heart rate (FHR) monitoring is routinely used in clinical practice to help obstetricians assess fetal health status during delivery. However, early detection of fetal acidosis that allows relevant decisions for operative delivery remains a challenging task, receiving considerable attention. This contribution promotes sparse support vector machine classification that permits to select a small number of relevant features and to achieve efficient fetal acidosis detection. A comprehensive set of features is used for FHR description, including enhanced and computerized clinical features, frequency domain, and scaling and multifractal features, all computed on a large (1288 subjects) and well-documented database. The individual performance obtained for each feature independently is discussed first. Then, it is shown that the automatic selection of a sparse subset of features achieves satisfactory classification performance (sensitivity 0.73 and specificity 0.75, outperforming clinical practice). The subset of selected features (average depth of decelerations $\textrm {MAD}_{\rm dtrd}$ , baseline level $\beta _0$ , and variability $H$ ) receives simple interpretation in clinical practice. Intrapartum fetal acidosis detection is improved in several respects: A comprehensive set of features combining clinical, spectral, and scale-free dynamics is used; an original multivariate classification targeting both sparse feature selection and high performance is devised; state-of-the-art performance is obtained on a much larger database than that generally studied with description of common pitfalls in supervised classification performance assessments.

Sparse Support Vector Machine for Intrapartum Fetal Heart Rate Classification

Background. Computerized ST analysis of fetal electrocardiography (ECG) combined with cardiotochography (CTG) has been introduced for intrapartum monitoring and is the prevailing method when ST ana ...

https://obgyn.onlinelibrary.wiley.com/doi/pdf/10.1111/aogs.12009

Fetal monitoring with computerized ST analysis during labor: a systematic review and meta-analysis

Non-invasive fetal electrocardiography (NI-FECG) is a promising alternative continuous fetal monitoring method that has the potential to allow morphological analysis of the FECG. However, there are a number of challenges associated with the evaluation of morphological parameters from the NI-FECG, including low signal to noise ratio of the NI-FECG and methodological challenges for getting reference annotations and evaluating the accuracy of segmentation algorithms. This work aims to validate the measurement of the fetal QT interval in term laboring women using a NI-FECG electrocardiogram monitor. Fetal electrocardiogram data were recorded from 22 laboring women at term using the NI-FECG and an invasive fetal scalp electrode simultaneously. A total of 105 one-minute epochs were selected for analysis. Three pediatric electrophysiologists independently annotated individual waveforms and averaged waveforms from each epoch. The intervals measured on the averaged cycles taken from the NI-FECG and the fetal scalp electrode showed a close agreement; the root mean square error between all corresponding averaged NI-FECG and fetal scalp electrode beats was 13.6 ms, which is lower than the lowest adult root mean square error of 16.1 ms observed in related adult QT studies. These results provide evidence that NI-FECG technology enables accurate extraction of the fetal QT interval.

/pdf/evaluation-of-the-fetal-qt-interval-using-non-invasive-fetal-45fxz1xtxj.pdf

Evaluation of the fetal QT interval using non-invasive fetal ECG technology.

Objective
To evaluate the clinical use of ST analysis (STAN) for intrapartum monitoring of high-risk pregnancies.

Design
Prospective observational study.

Setting
University hospital, Norway, 2004–2008.

Population
Singleton pregnancies with a gestational age above 35+6 weeks.

Methods
Analysis of maternal and neonatal outcomes for all deliveries according to the method of intrapartum monitoring.

Main outcome measures
Prevalence of cord metabolic acidosis (pH  12 mmol/L).

Results
Of 23 203 deliveries, 6010 (25.9%) were monitored with STAN. Fetal blood sampling was performed in 146 (2.4%) of the 6010 cases. During the study period, the prevalence of cord metabolic acidosis and moderate cord acidosis (pH < 7.15) decreased in STAN-monitored deliveries from 1.4 to 0.3% (p = 0.01) and from 16.4 to 11.7% (p = 0.001), respectively. The prevalence of moderate and severe neonatal encephalopathy was 0.38%. In the birth population, the proportion of cesarean deliveries decreased from 10.1 to 8.8%. The risk of emergency cesarean section after STAN monitoring compared with those monitored with auscultation/cardiotocography was high (odds ratio 5.4, 95% confidence interval = 4.9–6.1) but remained stable during the study period.

Conclusions
ST analysis is a useful tool for identification of fetuses at risk of intrapartum hypoxia. Despite the restricted use of fetal blood sampling, we found a low proportion of cord metabolic acidosis and newborn morbidity.

https://obgyn.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1600-0412.2012.01528.x

Intrapartum monitoring of high-risk deliveries with ST analysis of the fetal electrocardiogram: an observational study of 6010 deliveries.

576: Evaluation of the fetal QT interval using non-invasive fetal ECG technology

Use of peripartum ST analysis of fetal electrocardiogram without blood sampling: a large prospective cohort study.

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Use of peripartum ST analysis of fetal electrocardiogram without blood sampling: a large prospective cohort study.