Normalized spectral power of fetal heart rate variability is associated with fetal scalp blood pH

Towards better reliability in fetal heart rate variability using time domain and spectral domain analyses. A new method for assessing fetal neurological state?

OBJECTIVES

Fetal heart rate variability (FHRV) has shown potential in fetal surveillance. Therefore, we aimed to evaluate the reliability of time domain and spectral domain parameters based on non-invasive fetal electrocardiography (NI-FECG).

METHOD

NI-FECG, with a sampling frequency of 1 kHz, was obtained in 75 healthy, singleton pregnant women between gestational age (GA) 20+0 to 41+0. The recording was divided into a) heart rate pattern (HRP) and b) periods fulfilling certain criteria of stationarity of RR-intervals, termed stationary heart rate pattern (SHRP). Within each recording, the first and the last time series from each HRP with less than 5% artifact correction were analyzed and compared. Standard deviation of normal-to-normal RR-intervals (SDNN), root mean square of successive differences (RMSSD), high frequency power (HF-power), low frequency power (LF-power), and LF-power/HF-power were performed. A multivariate mixed model was used and acceptable reliability was defined as intraclass correlation coefficient (ICC) ≥ 0.80 and a coefficient of variation (CV) ≤ 15%. Based on these results, the CV and ICC were computed if the average of two to six time series was used.

RESULTS

For GA 28+0 to 34+6, SDNN and RMSSD exhibited acceptable reliability (CV < 15%; ICC > 90%), whereas GA 35+0 to 41+0and 20+0 to 27+6 showed higher CVs. Spectral domain parameters also showed high CVs However, by using the mean value of two to six time series, acceptable reliability in SDNN, RMSSD and HF-power from GA 28+0 was achieved. Stationarity of RR-intervals showed high influence on reliability and SHRP was superior to HRP, whereas the length of the time series showed minor influence.

CONCLUSION

Acceptable reliability seems achievable in SDNN, RMSSD and HF-power from gestational week 28. However, stationarity of RR-intervals should be considered when selecting time series for analyses.

Fetal respiratory movements improve reliability of heart rate variability and suggest a coupling between fetal respiratory arrhythmia and vagal activity

Fetal heart rate variability (FHRV) reflects autonomic cardiac regulation. The autonomic nervous system constantly adjusts the heart rate to maintain homeostasis. By providing insight into the fetal autonomic state, FHRV has the potential to become an investigational and clinical instrument. However, the method needs standardization and the influence of fetal movements, including fetal respiratory movements, is not well explored. Therefore, in a highly standardized setting, the aim was to evaluate the association between fetal movements and fetal heart rate variability (FHRV) including their impact on reliability. Fetal heart rate was obtained by noninvasive fetal electrocardiography (NI-FECG) and fetal movements by simultaneous ultrasound scanning in 30 healthy singleton pregnant women on two occasions with a maximum interval of 7 days. The standard deviation of normal-to-normal RR-intervals (SDNN), root mean square of successive RR-interval differences (RMDDS), high-frequency power (HF-power), low-frequency power (LF-power), and LF/HF were measured. A multivariate mixed model was used and reliability was defined as acceptable by a coefficient of variance (CV) ≤15% and an intraclass correlation coefficient (ICC) ≥0.80. During time periods with fetal respiratory movements, the highest reliability was achieved. Intra- and inter-observer reliability measurements were very high (CV: 0-9%; ICC ≧ 0.86). Within the same recording, SDNN and RMSSD achieved acceptable reliability (CV: 14-15%; ICC ≧ 0.80). However, day-to-day reliability displayed high CV's. In time periods with fetal respiratory movements, as compared to periods with quiescence RMSSD and HF-power were higher (Ratio: 1.33-2.03) and LF/HF power lower (Ratio: 0.54). In periods with fetal body movements SDNN, RMSSD and HF-power were higher (Ratio: 1.27-1.65). In conclusion, time periods with fetal respiratory movements were associated with high reliability of FHRV analyses and the highest values of parameters supposed to represent vagal activity.

Epileptic seizure onset predicts its duration

BACKGROUND

Epilepsy is characterized by recurrent seizures that have a variety of manifestations. The severity of, and risks for patients associated with, seizures are largely linked to the duration of seizures. Methods that determine seizure duration based on seizure onsets could be used to help mitigate the risks associated with what might be extended seizures by guiding timely interventions.

METHODS

Using long-term intracranial electroencephalography (iEEG) recordings, this article presents a method for predicting whether a seizure is going to be long or short by analyzing the seizure onset. The definition of long and short depends on each patient's seizure distribution. By analyzing 2954 seizures from 10 patients, patient-specific classifiers were built to predict seizure duration given the first few seconds from the onset.

RESULTS

The proposed methodology achieved an average area under the receiver operating characteristic curve (AUC) performance of 0.7 for the 5 of 10 patients with above chance prediction performance (p value from 0.04 to 10^-9 ).

CONCLUSIONS

Our results imply that the duration of seizures can be predicted from the onset in some patients. This could form the basis of methods for predicting status epilepticus or optimizing the amount of electrical stimulation delivered by seizure control devices.

The Noninvasive Fetal Electrocardiogram During Labor: A Review of the Literature

Importance

The introduction of the cardiotocogram (CTG) during labor has not been found to improve neonatal outcome. The search for a more reliable, less invasive, and patient-friendly technique is ongoing. The noninvasive fetal electrocardiogram (NI-fECG) has been proposed as one such alternative.

Objectives

The aim of this study was to review the literature on the performance of NI-fECG for fetal monitoring during labor. Following the PRISMA guidelines, a systematic search in MEDLINE, EMBASE, and Cochrane Library was performed. Studies involving original research investigating the performance of NI-fECG during labor were included. Animal studies and articles in languages other than English, Dutch, or German were excluded. The QUADAS-2 checklist was used for quality assessment. A descriptive analysis of the results is provided.

Results

Eight articles were included. Pooled analysis of the results of the separate studies was not possible due to heterogeneity. All studies demonstrate that it is possible to apply NI-fECG during labor. Compared with Doppler ultrasound, NI-fECG performs equal or better in most studies.

Conclusions and Relevance

NI-fECG for fetal monitoring is a promising noninvasive and patient-friendly technique that provides accurate information. Future studies should focus on signal quality throughout labor, with the aim to further optimize technical development of NI-fECG.

Systematic Review of Intrapartum Fetal Heart Rate Spectral Analysis and an Application in the Detection of Fetal Acidemia

It is fundamental to diagnose fetal acidemia as early as possible, allowing adequate obstetrical interventions to prevent brain damage or perinatal death. The visual analysis of cardiotocography traces has been complemented by computerized methods in order to overcome some of its limitations in the screening of fetal hypoxia/acidemia. Spectral analysis has been proposed by several studies exploring fetal heart rate recordings while referring to a great variety of frequency bands for integrating the power spectrum. In this paper, the main goal was to systematically review the spectral bands reported in intrapartum fetal heart rate studies and to evaluate their performance in detecting fetal acidemia/hypoxia. A total of 176 articles were reviewed, from MEDLINE, and 26 were included for the extraction of frequency bands and other relevant methodological information. An open-access fetal heart rate database was used, with recordings of the last half an hour of labor of 246 fetuses. Four different umbilical artery pH cutoffs were considered for fetuses' classification into acidemic or non-acidemic: 7.05, 7.10, 7.15, and 7.20. The area under the receiver operating characteristic curve (AUROC) was used to quantify the frequency bands' ability to distinguish acidemic fetuses. Bands referring to low frequencies, mainly associated with neural sympathetic activity, were the best at detecting acidemic fetuses, with the more severe definition (pH ≤ 7.05) attaining the highest values for the AUROC. This study shows that the power spectrum analysis of the fetal heart rate is a simple and powerful tool that may become an adjunctive method to CTG, helping healthcare professionals to accurately identify fetuses at risk of intrapartum hypoxia and to implement timely obstetrical interventions to reduce the incidence of related adverse perinatal outcomes.

Heart Rate Variability in the Perinatal Period: A Critical and Conceptual Review

Neonatal intensive care units (NICUs) greatly expand the use of technology. There is a need to accurately diagnose discomfort, pain, and complications, such as sepsis, mainly before they occur. While specific treatments are possible, they are often time-consuming, invasive, or painful, with detrimental effects for the development of the infant. In the last 40 years, heart rate variability (HRV) has emerged as a non-invasive measurement to monitor newborns and infants, but it still is underused. Hence, the present paper aims to review the utility of HRV in neonatology and the instruments available to assess it, showing how HRV could be an innovative tool in the years to come. When continuously monitored, HRV could help assess the baby’s overall wellbeing and neurological development to detect stress-/pain-related behaviors or pathological conditions, such as respiratory distress syndrome and hyperbilirubinemia, to address when to perform procedures to reduce the baby’s stress/pain and interventions, such as therapeutic hypothermia, and to avoid severe complications, such as sepsis and necrotizing enterocolitis, thus reducing mortality. Based on literature and previous experiences, the first step to efficiently introduce HRV in the NICUs could consist in a monitoring system that uses photoplethysmography, which is low-cost and non-invasive, and displays one or a few metrics with good clinical utility. However, to fully harness HRV clinical potential and to greatly improve neonatal care, the monitoring systems will have to rely on modern bioinformatics (machine learning and artificial intelligence algorithms), which could easily integrate infant’s HRV metrics, vital signs, and especially past history, thus elaborating models capable to efficiently monitor and predict the infant’s clinical conditions. For this reason, hospitals and institutions will have to establish tight collaborations between the obstetric, neonatal, and pediatric departments: this way, healthcare would truly improve in every stage of the perinatal period (from conception to the first years of life), since information about patients’ health would flow freely among different professionals, and high-quality research could be performed integrating the data recorded in those departments.

Doppler Ultrasound Technology for Fetal Heart Rate Monitoring: A Review

Fetal well-being is commonly assessed by monitoring the fetal heart rate (fHR). In clinical practice, the de facto standard technology for fHR monitoring is based on the Doppler ultrasound (US). Continuous monitoring of the fHR before and during labor is performed using a US transducer fixed on the maternal abdomen. The continuous fHR monitoring, together with simultaneous monitoring of the uterine activity, is referred to as cardiotocography (CTG). In contrast, for intermittent measurements of the fHR, a handheld Doppler US transducer is typically used. In this article, the technology of Doppler US for continuous fHR monitoring and intermittent fHR measurements is described, with emphasis on fHR monitoring for CTG. Special attention is dedicated to the measurement environment, which includes the clinical setting in which fHR monitoring is commonly performed. In addition, to understand the signal content of acquired Doppler US signals, the anatomy and physiology of the fetal heart and the surrounding maternal abdomen are described. The challenges encountered in these measurements have led to different technological strategies, which are presented and critically discussed, with a focus on the US transducer geometry, Doppler signal processing, and fHR extraction methods.

Independent Analysis of Decelerations and Resting Periods through CEEMDAN and Spectral-Based Feature Extraction Improves Cardiotocographic Assessment

Fetal monitoring is commonly based on the joint recording of the fetal heart rate (FHR) and uterine contraction signals obtained with a cardiotocograph (CTG). Unfortunately, CTG analysis is difficult, and the interpretation problems are mainly associated with the analysis of FHR decelerations. From that perspective, several approaches have been proposed to improve its analysis; however, the results obtained are not satisfactory enough for their implementation in clinical practice. Current clinical research indicates that a correct CTG assessment requires a good understanding of the fetal compensatory mechanisms. In previous works, we have shown that the complete ensemble empirical mode decomposition with adaptive noise, in combination with time-varying autoregressive modeling, may be useful for the analysis of those characteristics. In this work, based on this methodology, we propose to analyze the FHR deceleration episodes separately. The main hypothesis is that the proposed feature extraction strategy applied separately to the complete signal, deceleration episodes, and resting periods (between contractions), improves the CTG classification performance compared with the analysis of only the complete signal. Results reveal that by considering the complete signal, the classification performance achieved 81.7% quality. Then, including information extracted from resting periods, it improved to 83.2%.

Fetal Heart Rate Monitoring Implemented by Dynamic Adaptation of Transmission Power of a Flexible Ultrasound Transducer Array

Fetal heart rate (fHR) monitoring using Doppler Ultrasound (US) is a standard method to assess fetal health before and during labor. Typically, an US transducer is positioned on the maternal abdomen and directed towards the fetal heart. Due to fetal movement or displacement of the transducer, the relative fetal heart location (fHL) with respect to the US transducer can change, leading to frequent periods of signal loss. Consequently, frequent repositioning of the US transducer is required, which is a cumbersome task affecting clinical workflow. In this research, a new flexible US transducer array is proposed which allows for measuring the fHR independently of the fHL. In addition, a method for dynamic adaptation of the transmission power of this array is introduced with the aim of reducing the total acoustic dose transmitted to the fetus and the associated power consumption, which is an important requirement for application in an ambulatory setting. The method is evaluated using an in-vitro setup of a beating chicken heart. We demonstrate that the signal quality of the Doppler signal acquired with the proposed method is comparable to that of a standard, clinical US transducer. At the same time, our transducer array is able to measure the fHR for varying fHL while only using 50% of the total transmission power of standard, clinical US transducers.

The fetal electrocardiogram to detect the effects of betamethasone on fetal heart rate variability

BACKGROUND

Betamethasone is widely used to enhance fetal lung maturation in case of threatened preterm birth. Antenatal corticosteroids are known to reduce fetal heart rate variability (fHRV) in the days following administration. Since decreased fHRV is a marker for fetal distress, this transient decrease of fHRV can cause unnecessary medical intervention.

AIM

To describe the effect of betamethasone on fHRV, by applying spectral analysis on non-invasive fetal electrocardiogram (fECG) recordings.

STUDY DESIGN

Secondary analysis of a prospective cohort study.

SUBJECTS

Women with a singleton pregnancy, at risk for preterm delivery and receiving betamethasone, admitted to the obstetric high care unit in the period from March 2013 until July 2016.

OUTCOME MEASURES

The primary outcome measure was fHRV in both time- and frequency-domain. Secondary outcome measures included basal fetal heart rate (fHR) and fHR variance. FHRV parameters were then calculated separately for the quiet and active state.

RESULTS

Following 68 inclusions, 22 patients remained with complete series of measurements and sufficient data quality. FHRV parameters and fHR showed a decrease on day 2 compared to day 1, significant for short-term variability and high-frequency power. Similar results were found when analyzing for separate behavioral states. The number of segments in quiet state increased during days 1 and 2. Normalized values showed no difference for all behavioral states.

CONCLUSION

FHRV decreases on day 2 after betamethasone administration, while periods of fetal quiescence increase. No changes were found in the normalized values, indicating that the influence of autonomic modulation is minor. Clinical trial registration number NL43294.015.13.

Parasympathetic nervous system response to acidosis: Evaluation in an experimental fetal sheep model

INTRODUCTION

Heart rate variability and fetal heart rate decelerations are impacted by parasympathetic function and reflect acid-base status. Our team developed a new heart rate variability index, the fetal stress index (FSI), which has lower interindividual variability and higher sensitivity for detecting fluctuations in parasympathetic nervous system activity. The aim of this study was to explore the ability of the FSI to predict fetal acidosis in a fetal sheep model.

MATERIAL AND METHODS

Repeated 1-minute total umbilical cord occlusions (UCOs) were performed every 2.5 minutes over 3 hours to generate fetal acidosis mimicking that which occurs during labor and contractions. Fetal hemodynamic parameters, blood gas, the FSI and the magnitude (from the beginning to the nadir) of the fetal heart rate deceleration were recorded at regular intervals. The data were analyzed over three time intervals because of variation in the duration of the experiments: period A (first 12 UCOs), period B (middle 12 UCOs) and period C (last 12 UCOs).

RESULTS

Nine experiments were performed. Acidosis was progressive with a significant difference between the pH, lactate levels and base deficit values for the three periods of occlusion (P < 0.05). Both FSI and the magnitude of fetal heart rate decelerations gradually increased during the UCOs and both differed significantly between periods A and C (P = 0.0008 for FSI and P = 0.003 for deceleration).

CONCLUSION

This experimental protocol allowed the development of progressive acidosis in a good model of the physiology of labor. Parasympathetic nervous system activity increased during acidosis and could be measured using our index, the FSI, and the magnitude of fetal heart rate decelerations.

The influence of betamethasone on fetal heart rate variability, obtained by non-invasive fetal electrocardiogram recordings

BACKGROUND

Betamethasone is widely used to enhance fetal lung maturation in case of threatened preterm labour. Fetal heart rate variability is one of the most important parameters to assess in fetal monitoring, since it is a reliable indicator for fetal distress.

AIM

To describe the effect of betamethasone on fetal heart rate variability, by applying spectral analysis on non-invasive fetal electrocardiogram recordings.

STUDY DESIGN

Prospective cohort study.

SUBJECTS

Patients that require betamethasone, with a gestational age from 24 weeks onwards.

OUTCOME MEASURES

Fetal heart rate variability parameters on day 1, 2, and 3 after betamethasone administration are compared to a reference measurement.

RESULTS

Following 68 inclusions, 12 patients remained with complete series of measurements and sufficient data quality. During day 1, an increase in absolute fetal heart rate variability values was seen. During day 2, a decrease in these values was seen. All trends indicate to return to pre-medication values on day 3. Normalised high- and low-frequency power show little changes during the study period.

CONCLUSIONS

The changes in fetal heart rate variability following betamethasone administration show the same pattern when calculated by spectral analysis of the fetal electrocardiogram, as when calculated by cardiotocography. Since normalised spectral values show little changes, the influence of autonomic modulation seems minor.

Detection rate of fetal distress using contraction-dependent fetal heart rate variability analysis

OBJECTIVE

Monitoring of the fetal condition during labor is currently performed by cardiotocograpy (CTG). Despite the use of CTG in clinical practice, CTG interpretation suffers from a high inter- and intra-observer variability and a low specificity. In addition to CTG, analysis of fetal heart rate variability (HRV) has been shown to provide information on fetal distress. However, fetal HRV can be strongly influenced by uterine contractions, particularly during the second stage of labor. Therefore, the aim of this study is to examine if distinguishing contractions from rest periods can improve the detection rate of HRV features for fetal distress during the second stage of labor.

APPROACH

We used a dataset of 100 recordings, containing 20 cases of fetuses with adverse outcome. The most informative HRV features were selected by a genetic algorithm and classification performance was evaluated using support vector machines.

MAIN RESULTS

Classification performance of fetal heart rate segments closest to birth improved from a geometric mean of 70% to 79%. If the classifier was used to indicate fetal distress over time, the geometric mean at 15 minutes before birth improved from 60% to 72%.

SIGNIFICANCE

Our results show that combining contraction-dependent HRV features with HRV features calculated over the entire fetal heart rate signal improves the detection rate of fetal distress.

Correlation of a new index reflecting the fluctuation of parasympathetic tone and fetal acidosis in an experimental study in a sheep model

The autonomic nervous system plays a leading role in the control of fetal homeostasis. Fetal heart rate variability (HRV) analysis is a reflection of its activity. We developed a new index (the Fetal Stress Index, FSI) reflecting parasympathetic tone. The objective of this study was to evaluate this index as a predictor of fetal acid-base status. This was an experimental study on chronically instrumented fetal lambs (n = 11, surgery at 128 +/- 2 days gestational age, term = 145 days). The model was based on 75% occlusion of the umbilical cord for a maximum of 120 minutes or until an arterial pH ≤ 7.20 was reached. Hemodynamic, gasometric and FSI parameters were recorded throughout the experimentation. We studied the FSI during the 10 minutes prior to pH samplings and compared values for pH>7.20 and pH≤ 7.20. In order to analyze the FSI evolution during the 10 minutes periods, we analyzed the minimum, maximum and mean values of the FSI (respectively FSImin, FSImax and FSImean) over the periods. 11 experimentations were performed. During occlusion, the heart rate dropped with an increase in blood pressure (respectively 160(155-182) vs 106(101-120) bpm and 42(41-45) vs 58(55-62) mmHg after occlusion). The FSImin was 38.6 (35.2-43.3) in the group pH>7.20 and was higher in the group pH less than 7.20 (46.5 (43.3-52.0), p = 0.012). The correlation of FSImin was significant for arterial pH (coefficient of -0.671; p = 0.004) and for base excess (coefficient of -0.632; p = 0.009). The correlations were not significant for the other parameters. In conclusion, our new index seems well correlated with the fetal acid-base status. Other studies must be carried out in a situation close to the physiology of labor by sequential occlusion of the cord.

Parasympathetic tone variations according to umbilical cord pH at birth: a computerized fetal heart rate variability analysis

Non-reassuring fetal heart rate tracings reflect an imbalance between the parasympathetic and sympathetic nervous systems. In this situation, fetal asphyxia can be suspected and may be confirmed by metabolic measurements at birth like low pH or high base deficit values. The objective of this study was to determine whether fetal asphyxia during labor is related to parasympathetic nervous system activity. This is a retrospective study of a database collected in 5 centers. Two hundred and ninety-nine fetal heart rate tracings collected during labor were analyzed. Autonomic nervous system, especially the parasympathetic nervous system, was analyzed using an original index: the FSI (Fetal Stress Index). The FSI is a parasympathetic activity evaluation based on fetal heart rate variability analysis. Infants were grouped based on normal or low pH value at birth. FSI was measured during the last 30 min of labor before birth and compared between groups. The minimum value of the FSI during the last 30 min before delivery was significantly lower in the group with the lower umbilical cord arterial pH value. In this pilot study during labor, FSI was lower in the group of infants with low arterial pH at birth.

Using uterine activity to improve fetal heart rate variability analysis for detection of asphyxia during labor

During labor, uterine contractions can cause temporary oxygen deficiency for the fetus. In case of severe and prolonged oxygen deficiency this can lead to asphyxia. The currently used technique for detection of asphyxia, cardiotocography (CTG), suffers from a low specificity. Recent studies suggest that analysis of fetal heart rate variability (HRV) in addition to CTG can provide information on fetal distress. However, interpretation of fetal HRV during labor is difficult due to the influence of uterine contractions on fetal HRV. The aim of this study is therefore to investigate whether HRV features differ during contraction and rest periods, and whether these differences can improve the detection of asphyxia. To this end, a case-control study was performed, using 14 cases with asphyxia that were matched with 14 healthy fetuses. We did not find significant differences for individual HRV features when calculated over the fetal heart rate without separating contractions and rest periods (p  >  0.30 for all HRV features). Separating contractions from rest periods did result in a significant difference. In particular the ratio between HRV features calculated during and outside contractions can improve discrimination between fetuses with and without asphyxia (p  <  0.04 for three out of four ratio HRV features that were studied in this paper).

Reliability of spectral analysis of fetal heart rate variability

Spectral analysis of fetal heart rate variability could provide information on fetal wellbeing. Unfortunately, fetal heart rate recordings are often contaminated by artifacts. Correction of these artifacts affects the outcome of spectral analysis, but it is currently unclear what level of artifact correction facilitates reliable spectral analysis. In this study, a method is presented that estimates the error in spectral powers due to artifact correction, based on the properties of the Continuous Wavelet Transformation. The results show that it is possible to estimate the error in spectral powers. The information about this error makes it possible for clinicians to assess the reliability of spectral analysis of fetal heart rate recordings that are contaminated by artifacts.

An efficient seizure prediction method using KNN-based undersampling and linear frequency measures

Seizure prediction based on analysis of electroencephalogram signals has generated considerable research interests. A reliable seizure prediction algorithm with minimal computational requirements is prominent issue for medical facilities; however, it has not been addressed correctly. In this study, an optimized novel method is proposed in order to remove computational complexity, and predict epileptic seizures clinically. It is based on the univariate linear features in eight frequency sub-bands. It also employs principal component analysis (PCA) for dimension reduction and optimal feature selection. Class unbalanced problem is tackled by K-nearest neighbor (KNN)-based undersampling combined with support vector machine (SVM) classifier. To find out the best results two types of postprocessing methods were studied. The proposed algorithm was evaluated on seizures and 434.9h of interictal data from 18 patients of Freiburg database. It predicted 100% of seizures with average false alarm rate of 0.13 per hour ranging between 0 and 0.39. Furthermore, G-Mean and F-measure were used for validation which were 0.97 and 0.90, respectively. These results confirmed the discriminative ability of the algorithm. In comparison with other studies, the proposed method improves trade-off between sensitivity and false prediction rate with linear features and low computational requirements and it can potentially be employed in implantable devices. Achieving high performance by linear features, PCA, KNN-based undersampling, and SVM demonstrates that this method can potentially be used in implantable devices.

Fetal heart rate variability during pregnancy, obtained from non-invasive electrocardiogram recordings

OBJECTIVE

Non-invasive spectral analysis of fetal heart rate variability is a promising new field of fetal monitoring. To validate this method properly, we studied the relationship between gestational age and the influence of fetal rest-activity state on spectral estimates of fetal heart rate variability.

DESIGN

Prospective longitudinal study.

SETTING

Tertiary care teaching hospital.

POPULATION

Forty healthy women with an uneventful singleton pregnancy.

METHODS

Non-invasive fetal electrocardiogram measurements via the maternal abdomen were performed at regular intervals between 14 and 40 weeks of gestation and processed to detect beat-to-beat fetal heart rate. Simultaneous ultrasound recordings were performed to assess fetal rest-activity state.

MAIN OUTCOME MEASURES

Absolute and normalized power of fetal heart rate variability in the low (0.04-0.15 Hz) and high (0.4-1.5 Hz) frequency band were obtained, using Fourier Transform.

RESULTS

14% of all measurements and 3% of the total amount of abdominal data (330 segments) was usable for spectral analysis. During 21-30 weeks of gestation, a significant increase in absolute low and high frequency power was observed. During the active state near term, absolute and normalized low frequency power were significantly higher and normalized high frequency power was significantly lower compared with the quiet state.

CONCLUSIONS

The observed increase in absolute spectral estimates in preterm fetuses was probably due to increased sympathetic and parasympathetic modulation and might be a sign of autonomic development. Further improvements in signal processing are needed before this new method of fetal monitoring can be introduced in clinical practice.

Do spectral bands of fetal heart rate variability associate with concomitant fetal scalp pH?

BACKGROUND

Objective information on specific fetal heart rate (FHR) parameters would be advantageous when assessing fetal responses to hypoxia. Small, visually undetectable changes in FHR variability can be quantified by power spectral analysis of FHR variability.

AIMS

To investigate the effect of intrapartum hypoxia and acidemia on spectral powers of FHR variability.

STUDY DESIGN

This is a retrospective observational clinical study with data from an EU multicenter project.

SUBJECTS

We had 462 fetuses with a normal pH-value (pH>7.20; controls) in fetal scalp blood sample (FBS) and 81 fetuses with a low scalp pH-value (≤ 7.20; low-FBS pH-fetuses). The low-FBS pH-fetuses were further divided into two subgroups according to the degree of acidemia: fetuses with FBS pH7.11-7.20 (n = 58) and fetuses with FBS pH ≤7.10 (n = 23).

OUTCOME MEASURES

Spectral powers of FHR variability in relation to the concomitant FBS pH-value.

RESULTS

Fetuses with FBS pH ≤7.20 had increased spectral powers of FHR variability compared with controls (2.49 AU vs. 2.23 AU; p = 0.038). However, the subgroup of most affected fetuses (those with FBS pH ≤7.10) had significantly lower FHR variability spectral powers when compared to fetuses with FBS pH7.11-7.20.

CONCLUSIONS

This study shows that spectral powers of FHR variability change as a fetus becomes hypoxic, and that spectral powers decrease with deepening fetal acidemia.

Epileptic seizure prediction based on a bivariate spectral power methodology

The spectral power of 5 frequently considered frequency bands (Alpha, Beta, Gamma, Theta and Delta) for 6 EEG channels is computed and then all the possible pairwise combinations among the 30 features set, are used to create a 435 dimensional feature space. Two new feature selection methods are introduced to choose the best candidate features among those and to reduce the dimensionality of this feature space. The selected features are then fed to Support Vector Machines (SVMs) that classify the cerebral state in preictal and non-preictal classes. The outputs of the SVM are regularized using a method that accounts for the classification dynamics of the preictal class, also known as "Firing Power" method. The results obtained using our feature selection approaches are compared with the ones obtained using minimum Redundancy Maximum Relevance (mRMR) feature selection method. The results in a group of 12 patients of the EPILEPSIAE database, containing 46 seizures and 787 hours multichannel recording for out-of-sample data, indicate the efficiency of the bivariate approach as well as the two new feature selection methods. The best results presented sensitivity of 76.09% (35 of 46 seizures predicted) and a false prediction rate of 0.15(-1).