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Electronic fetal heart rate (FHR) monitoring is a technical means to evaluate the state of the fetus in the uterus by monitoring FHR. The main purpose is to detect intrauterine hypoxia and take corresponding medical measures timely. Because the fetus sleeps quietly for up to 1 hour sometimes, ultrasound Doppler is not easy to continuously detect for a long time. The electronic fetal monitor obtains the fetal heart rate, which not only improves the accuracy and comfort, but also the convenient implementation of long-term monitoring. It is beneficial to reduce perinatal fetal morbidity and mortality. This study used maternal–fetal Holter monitor which is based on the technology of fetal electrocardiograph (FECG) to collect the FHR, and then design algorithm to extract the baseline FHR, acceleration, variation, sleep-wake cycle and nonlinear parameters. There were significant differences in the 22 parameters between the normal and the suspicious group. Using the 22 characteristic parameters, the support vector machine was used to classify the normal and the suspected group of fetuses. 80% of the data was used to train a classification model. The remaining 20% of the data was used as a test set and its accuracy reached 93.75%. [ABSTRACT FROM AUTHOR]

Cardiotocography (CTG) is the basic method of monitoring foetal condition in the perinatal period. However, due to the limited insight into the CTG generation mechanism, some CTG recordings can be mistreated as a predictor of neonatal asphyxia, leading to a wrong assessment of the foetal status and improper obstetric intervention. Therefore, in case of suspicious CTG indications, a reliable verification of the true foetal status is vital for reducing the clinical diagnosis false-positive rate and avoiding the unnecessary obstetrician intervention. The paper presents the results obtained for 44 foetuses on the shares of three heart rate variation (HRV) ranges and quiet sleep cycles. This approach uses the parameters of the HRV range shares and quiet sleep cycles to analyse different types of foetuses. The results obtained show that most parameters reveal significant differences between normal and suspicious groups. This is quite lucrative for defining a set of coefficients, whose incorporation into a classifier will improve the accuracy of distinguishing the normal foetuses from suspicious ones. [ABSTRACT FROM AUTHOR]

Background: Fetal electrocardiography (FECG) places electrodes on the maternal abdomen to convert the fetal electrocardiosignals into fetal heart rate (FHR), improving the accuracy and comfort of pregnant woman. At the same time, FECG simplifies the procedure of long term monitoring in the perinatal period.Objective: Investigating the influence of gestational age and time of day on FHR features to distinguish between non-stress test (NST) normal fetuses and NST suspicious fetuses.Methods: A novel method of FHR baseline estimation was presented; then baseline value and fetal heart rate variation (FHRV) were analyzed in the time domain using FHR signals recorded from 52 fetuses.Results: Baseline values in 1:00, 2:00, 4:00, 5:00 and heart rate variation (HRV) distribution showed a significant difference (p< 0.05) between NST normal fetuses and NST suspicious fetuses.Conclusions: The results suggest that NST normal and suspicious fetuses had same outcome and different FHR features. Accurately distinguishing normal fetuses and suspicious fetuses is important for lowering the false positive rate and reducing unnecessary clinical intervention. [ABSTRACT FROM AUTHOR]

Non-stress testing (NST) is the primary method of determining fetal condition during the perinatal period, and as such, has high specificity. However, short-term monitoring and visual inspection of the cardiotocogram demonstrates several limitations in understanding fetal status which can be mistaken as predictors of neonatal asphyxia. Fetal electrocardiography (FECG) is a novel, long-term monitoring method which can reflect more objective and accurate fetal information. This article presents experimental results of four fetal heart rate (FHR) acceleration features of 44 fetuses extracted from FECG. The novelty of this approach lies in its combined use of parameters which can express both duration and amplitude of heart rate acceleration. Results demonstrate that most parameters significantly differ between normal fetuses and fetuses with suspected abnormalities. Results are promising for the identification of a set or parameters which may be used as classifiers to improve the success rate when distinguishing between normal and abnormal fetuses. [ABSTRACT FROM PUBLISHER]

Fetal ECG can be obtained in a non-invasive manner to monitor fetal growth status. In this study, a fetal heart rate calculation system was proposed, which consists of the fetal ECG recorder (MF-HOLTER) and the fetal ECG monitoring software (FECG-MS). The abdomen electrocardiogram (AECG) of pregnant woman is acquired through the MF-HOLTER. The FECG-MS packs the AECG data and calls the fetal ECG separation algorithm to obtain the separated FECG and the fetal QRS (FQRS) position. The fetal heart rate (FHR) is further obtained by calculating the R-R interval value. At the same time, this study proposed a FQRS position correction algorithm to calculate the correct FHR value. In order to verify the accuracy of the FHR calculation, the ECG signal of FLUKE’s PS320 FETAL SIMULATOR and clinical data were simultaneously tested. The accuracy rate is over 98% in processing the simulator’s data. In processing clinical data, the FHR values obtained by both the system proposed in this study and Monica AN24 are very close, and the difference is less than 1 bpm. The results show that the fetal heart rate calculation system is accurate and stable, and has a positive application value and prospect. [ABSTRACT FROM AUTHOR]