Spectral analysis of antepartum heart rate variability

Cardiotocography signal abnormality classification using time-frequency features and Ensemble Cost-sensitive SVM classifier

BACKGROUND

Cardiotocography (CTG) signal abnormality classification plays an important role in the diagnosis of abnormal fetuses. This classification problem is made difficult by the non-stationary nature of CTG and the dataset imbalance. This paper introduces a novel application of Time-frequency (TF) features and Ensemble Cost-sensitive Support Vector Machine (ECSVM) classifier to tackle these problems.

METHODS

Firstly, CTG signals are converted into TF-domain representations by Continuous Wavelet Transform (CWT), Wavelet Coherence (WTC), and Cross-wavelet Transform (XWT). From these representations, a novel image descriptor is used to extract the TF features. Then, the linear feature is derived from the time-domain representation of the CTG signal. The linear and TF features are fed to the ECSVM classifier for prediction and classification of fetal outcome.

RESULTS

The TF features show the significant difference (p-value<0.05) in distinguishing abnormal CTG signals, but not for traditional nonlinear features. In ECSVM abnormality classification, using only linear features, the sensitivity, specificity, and quality index are 59.3%, 78.3%, and 68.1%, respectively, whereas more effective results (sensitivity: 85.2%, specificity: 66.1%, and quality index: 75.0%) are obtained using a combination of linear and TF features, with a performance improvement index of 10.1%. Especially, the area under the receiver operating characteristic curve (0.77 vs. 0.64) is significantly increased with the ECSVM vs. SVM.

CONCLUSION

Our method can greatly improve the classification results, especially for sensitivity. It improves the true positive rate of CTG abnormality classification and reduces the false positive rate, which may help detect and treat abnormal fetuses during labor.

A Strategy for Classification of "Vaginal vs. Cesarean Section" Delivery: Bivariate Empirical Mode Decomposition of Cardiotocographic Recordings

We propose objective and robust measures for the purpose of classification of "vaginal vs. cesarean section" delivery by investigating temporal dynamics and complex interactions between fetal heart rate (FHR) and maternal uterine contraction (UC) recordings from cardiotocographic (CTG) traces. Multivariate extension of empirical mode decomposition (EMD) yields intrinsic scales embedded in UC-FHR recordings while also retaining inter-channel (UC-FHR) coupling at multiple scales. The mode alignment property of EMD results in the matched signal decomposition, in terms of frequency content, which paves the way for the selection of robust and objective time-frequency features for the problem at hand. Specifically, instantaneous amplitude and instantaneous frequency of multivariate intrinsic mode functions are utilized to construct a class of features which capture nonlinear and nonstationary interactions from UC-FHR recordings. The proposed features are fed to a variety of modern machine learning classifiers (decision tree, support vector machine, AdaBoost) to delineate vaginal and cesarean dynamics. We evaluate the performance of different classifiers on a real world dataset by investigating the following classifying measures: sensitivity, specificity, area under the ROC curve (AUC) and mean squared error (MSE). It is observed that under the application of all proposed 40 features AdaBoost classifier provides the best accuracy of 91.8% sensitivity, 95.5% specificity, 98% AUC, and 5% MSE. To conclude, the utilization of all proposed time-frequency features as input to machine learning classifiers can benefit clinical obstetric practitioners through a robust and automatic approach for the classification of fetus dynamics.

Frequency and Time Domain Analysis of Foetal Heart Rate Variability with Traditional Indexes: A Critical Survey

Monitoring of foetal heart rate and its variability (FHRV) covers an important role in assessing health of foetus. Many analysis methods have been used to get quantitative measures of FHRV. FHRV has been studied in time and in frequency domain and interesting clinical results have been obtained. Nevertheless, a standardized definition of FHRV and a precise methodology to be used for its evaluation are lacking. We carried out a literature overview about both frequency domain analysis (FDA) and time domain analysis (TDA). Then, by using simulated FHR signals, we defined the methodology for FDA. Further, employing more than 400 real FHR signals, we analysed some of the most common indexes, Short Term Variability for TDA and power content of the spectrum bands and sympathovagal balance for FDA, and evaluated their ranges of values, which in many cases are a novelty. Finally, we verified the relationship between these indexes and two important parameters: week of gestation, indicator of foetal growth, and foetal state, classified as active or at rest. Our results indicate that, according to literature, it is necessary to standardize the procedure for FHRV evaluation and to consider week of gestation and foetal state before FHR analysis.

Software for computerised analysis of cardiotocographic traces

Despite the widespread use of cardiotocography in foetal monitoring, the evaluation of foetal status suffers from a considerable inter and intra-observer variability. In order to overcome the main limitations of visual cardiotocographic assessment, computerised methods to analyse cardiotocographic recordings have been recently developed. In this study, a new software for automated analysis of foetal heart rate is presented. It allows an automatic procedure for measuring the most relevant parameters derivable from cardiotocographic traces. Simulated and real cardiotocographic traces were analysed to test software reliability. In artificial traces, we simulated a set number of events (accelerations, decelerations and contractions) to be recognised. In the case of real signals, instead, results of the computerised analysis were compared with the visual assessment performed by 18 expert clinicians and three performance indexes were computed to gain information about performances of the proposed software. The software showed preliminary performance we judged satisfactory in that the results matched completely the requirements, as proved by tests on artificial signals in which all simulated events were detected from the software. Performance indexes computed in comparison with obstetricians' evaluations are, on the contrary, not so satisfactory; in fact they led to obtain the following values of the statistical parameters: sensitivity equal to 93%, positive predictive value equal to 82% and accuracy equal to 77%. Very probably this arises from the high variability of trace annotation carried out by clinicians.

Computerized analysis of fetal heart rate variability signal during the stages of labor

AIM

To analyze computerized cardiotocographic (cCTG) parameters (baseline fetal heart rate, baseline FHR; short term variability, STV; approximate entropy, ApEn; low frequency, LF; movement frequency, MF; high frequency, HF) in physiological pregnancy in order to correlate them with the stages of labor. This could provide more information for understanding the mechanisms of nervous system control of FHR during labor progression.

METHODS

A total of 534 pregnant women were monitored on cCTG from the 37th week before the onset of spontaneous labor and during the first and the second stage of labor. Statistical analysis was performed using Kruskal-Wallis test and Wilcoxon rank-sum test with the Bonferroni adjusted α (< 0.05).

RESULTS

Statistically significant differences were seen between baseline FHR, MF and HF (P < 0.001), in which the first two were reduced and the third was increased when compared between pre-labor, and the first and second stages of labor. Differences between some of the stages were found for ApEn, LF and for LF/(HF + MF), where the first and the third were reduced and the second was increased.

CONCLUSIONS

cCTG modifications during labor may reflect the physiologic increased activation of the autonomous nervous system. Using computerized fetal heart rate analysis during labor it may be possible to obtain more information from the fetal cardiac signal, in comparison with the traditional tracing.

Multi-parametric heart rate analysis in premature babies exposed to sudden infant death syndrome

Severe premature babies present a risk profile higher than the normal population. Reasons are related to the incomplete development of physiological systems that support baby's life. Heart Rate Variability (HRV) analysis can help the identification of distress conditions as it is sensitive to Autonomic Nervous System (ANS) behavior. This paper presents results obtained in 35 babies with severe prematurity, in quiet and active sleep and in prone and supine position. HRV was analyzed in time and frequency domain and with nonlinear parameters. The novelty of this approach lies in the combined use of parameters generally adopted in fetal monitoring and "adult" indices. Results show that most parameters succeed in classifying different experimental conditions. This is very promising as our final objective is to identify a set of parameters that could be the basis for a risk classifier to improve the care path of premature population.

Assessment of coupling between trans-abdominally acquired fetal ECG and uterine activity by bivariate phase-rectified signal averaging analysis

Couplings between uterine contractions (UC) and fetal heart rate (fHR) provide important information on fetal condition during labor. At present, couplings between UC and fHR are assessed by visual analysis and interpretation of cardiotocography. The application of computerized approaches is restricted due to the non-stationarity of the signal, missing data and noise, typical for fHR. Herein, we propose a novel approach to assess couplings between UC and fHR, based on a signal-processing algorithm termed bivariate phase-rectified signal averaging (BPRSA).

Methods

Electrohysterogram (EHG) and fetal electrocardiogram (fECG) were recorded non-invasively by a trans-abdominal device in 73 women at term with uneventful singleton pregnancy during the first stage of labor. Coupling between UC and fHR was analyzed by BPRSA and by conventional cross power spectral density analysis (CPSD). For both methods, degree of coupling was assessed by the maximum coefficient of coherence (C_PRSA and C_RAW, respectively) in the UC frequency domain. Coherence values greater than 0.50 were consider significant. C_PRSA and C_RAW were compared by Wilcoxon test.

Results

At visual inspection BPRSA analysis identified coupled periodicities in 86.3% (63/73) of the cases. 11/73 (15%) cases were excluded from further analysis because no 30 minutes of fECG recording without signal loss was available for spectral analysis. Significant coupling was found in 90.3% (56/62) of the cases analyzed by BPRSA, and in 24.2% (15/62) of the cases analyzed by CPSD, respectively. The difference between median value of C_PRSA and C_RAW was highly significant (0.79 [IQR 0.69–0.90] and 0.29 [IQR 0.17–0.47], respectively; p<0.0001).

Conclusion

BPRSA is a novel computer-based approach that can be reliably applied to trans-abdominally acquired EHG-fECG. It allows the assessment of correlations between UC and fHR patterns in the majority of labors, overcoming the limitations of non-stationarity and artifacts. Compared to standard techniques of cross-correlations, such as CPSD, BPRSA is significantly superior.

Nonlinear analysis of heart rate variability to assess the reaction of ewe fetuses undergoing fetal cardiac surgery

Fetal cardiac surgery (FCS) represents a challenging issue for the in utero treatment of congenital heart defects. However, FCS has still not gained the sufficient reliability for clinical practice due to an incompletely elucidated fetal stress response. For example, blood sampling can contribute to its onset, leading to fetoplacental unit dysfunction, one of the main causes of failure of the surgical procedure. In order to address this issue, the role of the autonomic control system during an experimental procedure of cardiac bypass on ewe fetuses was investigated by means of recurrence quantification analysis (RQA), a well-recognized method for the analysis of nonlinear systems. RQA was applied to time series extracted from fetal arterial pressure recordings before and after the cardiac bypass established by means of an extracorporeal circuit, including an axial blood pump, and taking advantage of the capability of the placenta to work as a natural oxygenator. Statistically significant correlations were found among RQA-based metrics and fetal blood gas data, suggesting the possibility to infer the clinical status of the fetus starting from its hemodynamic signals.This study shows the relevance of RQA as a complementary tool for the monitoring of the fetal status during cardiac bypass.

A continuous wavelet transform-based method for time-frequency analysis of artefact-corrected heart rate variability data

Time-frequency analysis of heart rate variability (HRV) provides relevant clinical information. However, time-frequency analysis is very sensitive to artefacts. Artefacts that are present in heart rate recordings may be corrected, but this reduces the variability in the signal and therefore adversely affects the accuracy of calculated spectral estimates. To overcome this limitation of traditional techniques for time-frequency analysis, a new continuous wavelet transform (CWT)-based method was developed in which parts of the scalogram that have been affected by artefact correction are excluded from power calculations. The method was evaluated by simulating artefact correction on HRV data that were originally free of artefacts. Commonly used spectral HRV parameters were calculated by the developed method and by the short-time Fourier transform (STFT), which was used as a reference. Except for the powers in the very low-frequency and low-frequency (LF) bands, powers calculated by the STFT proved to be extremely sensitive to artefact correction. The CWT-based calculations in the high-frequency and very high-frequency bands corresponded well with their theoretical values. The standard deviations of these powers, however, increase with the number of corrected artefacts which is the result of the non-stationarity of the R-R interval series that were analysed. The powers calculated in the LF band turned out to be slightly sensitive to artefact correction, but the results were acceptable up to 20% artefact correction. Therefore, the CWT-based method provides a valuable alternative for the analysis of HRV data that cannot be guaranteed to be free of artefacts.

Complexity analysis of the fetal heart rate variability: early identification of severe intrauterine growth-restricted fetuses

The main goal of this work is to suggest new indices for a correct identification of the intrauterine growth-restricted (IUGR) fetuses on the basis of fetal heart rate (FHR) variability analysis performed in the antepartum period. To this purpose, we analyzed 59 FHR time series recorded in early periods of gestation through a Hewlett Packard 1351A cardiotocograph. Advanced analysis techniques were adopted including the computation of the Lempel Ziv complexity (LZC) index and the multiscale entropy (MSE), that is, the entropy estimation with a multiscale approach. A multiparametric classifier based on k-mean cluster analysis was also performed to separate pathological and normal fetuses. The results show that the proposed LZC and the MSE could be useful to identify the actual IUGRs and to separate them from the physiological fetuses, providing good values of sensitivity and accuracy (Se = 77.8%, Ac = 82.4%).

The effect of artifact correction on spectral estimates of heart rate variability

Spectral analysis of fetal heart rate variability might offer additional information that can be used for assessing the fetal condition more reliably. Clinical recordings of fetal heart rate are usually contaminated by artifacts. These artifacts can be detected and corrected or removed, but this can affect the spectral estimates obtained from the heart rate data. To determine what level of artifact correction is still acceptable for reliable calculation of spectral heart rate variability parameters, artifact correction is simulated on neonatal and fetal data that did originally not contain artifacts. 2000 data segments with various levels of artifact correction are analyzed spectrally, and calculated spectral estimates are compared to the values obtained from the original, artifact free data. In the very low ( 0.04 Hz) and low (0.04 - 0.15 Hz) frequency range, powers can be calculated reliably when up to 25% of the data are missing due to artifact correction. Powers in the high frequency range (0.15 - 0.4 Hz for adults, 0.4 - 1.5 Hz for newborns) cannot be calculated reliably when data are missing due to artifact correction. This is a major limitation for application in clinical practice, which might be solved by calculating power in the high frequency range at a shorter time scale than power in the low frequency range. Short segments of heart rate data that are free of artifacts can then be used to calculate powers in the high frequency range reliably, while segments that contain artifacts are excluded.

An algorithm for the recovery of fetal heart rate series from CTG data

Cardiotocography (simultaneous recording of fetal heart rate (FHR) and uterine contractions) is one of the most used diagnostic techniques to evaluate fetal well-being and to investigate the functional state of the fetal autonomic nervous system. Recently, great interest has been paid to the variability of the FHR, and its frequency analysis, as a base for a more objective analysis of the cardiotocographic (CTG) tracings. FHR signals are unevenly sampled series. To obtain evenly sampled series, cardiotocographs often use zero-order interpolation. Such process is simple and fast but results unsuitable for frequency analyses because it introduces alterations in the FHR power spectrum. An algorithm for the recovery of the true FHR series out of the zero-order interpolated CTG data was developed and evaluated.

Multiresolution Analysis of Heart Rate Variability as Investigational Tool in Experimental Fetal Cardiac Surgery

Multiresolution analysis of heart rate variability derived from aortic blood pressure, acquired before and after (30 and 60 min) experimental fetal cardiac bypass performed on five ewe's fetuses, was used to investigate the physiological response to an invasive clinical approach. Tachograms were implemented and analyzed by wavelet transform in order to verify the existence of a quantitative relationship between arterial blood gases and time series in the very-low (0.021<f<0.084 Hz) and low (0.084<f<0.337 Hz) frequency band. Multiresolution analysis showed an average decreasing trend from basal condition for all the fetuses investigated in the very-low frequency band, while an opposite trend was highlighted in the low frequency band: this resulting behavior could be related to the temporal evolution of blood gas data. Finally, a slight decrease of sympatho-vagal balance was monitored 30 min after the cardiac bypass was discontinued compared to basal condition. Multiresolution analysis could give more insights on fetal hypoxemia and could also represent a minimally invasive monitoring tool to limit the damage to the fetoplacental unit during experimental fetal cardiac surgery.

Foetal heart rate power spectrum response to uterine contraction

Cardiotocography is the most diffused prenatal diagnostic technique in clinical routine. The simultaneous recording of foetal heart rate (FHR) and uterine contractions (UC) provides useful information about foetal well-being during pregnancy and labour. However, foetal electronic monitoring interpretation still lacks reproducibility and objectivity. New methods of interpretation and new parameters can further support physicians' decisions. Besides common time-domain analysis, study of the variability of FHR can potentially reveal autonomic nervous system activity of the foetus. In particular, it is clinically relevant to investigate foetal reactions to UC to diagnose foetal distress early. Uterine contraction being a strong stimulus for the foetus and its autonomic nervous system, it is worth exploring the FHR variability response. This study aims to analyse modifications of the power spectrum of FHR variability corresponding to UC. Cardiotocographic signal tracts corresponding to 127 UC relative to 30 healthy foetuses were analysed. Results mainly show a general, statistically significant (t test, p<0.01) power increase of the FHR variability in the LF 0.03-0.2 Hz and HF 0.2-1 in correspondence of the contraction with respect to a reference tract set before contraction onset. Time evolution of the power within these bands was computed by means of time-varying spectral estimation to concisely show the FHR response along a uterine contraction. A synchronised grand average of these responses was also computed to verify repeatability, using the contraction apex as time reference. Such modifications of the foetal HRV that follow a contraction can be a sign of ANS reaction and, therefore, additional, objective information about foetal reactivity during labour.

Linear and nonlinear parameters for the analysis of fetal heart rate signal from cardiotocographic recordings

Antepartum fetal monitoring based on the classical cardiotocography (CTG) is a noninvasive and simple tool for checking fetal status. Its introduction in the clinical routine limited the occurrence of fetal problems leading to a reduction of the precocious child mortality. Nevertheless, very poor indications on fetal pathologies can be inferred from the even automatic CTG analysis methods, which are actually employed. The feeling is that fetal heart rate (FHR) signals and uterine contractions carry much more information on fetal state than is usually extracted by classical analysis methods. In particular, FHR signal contains indications about the neural development of the fetus. However, the methods actually adopted for judging a CTG trace as "abnormal" give weak predictive indications about fetal dangers. We propose a new methodological approach for the CTG monitoring, based on a multiparametric FHR analysis, which includes spectral parameters from autoregressive models and nonlinear algorithms (approximate entropy). This preliminary study considers 14 normal fetuses, eight cases of gestational (maternal) diabetes, and 13 intrauterine growth retarded fetuses. A comparison with the traditional time domain analysis is also included. This paper shows that the proposed new parameters are able to separate normal from pathological fetuses. Results constitute the first step for realizing a new clinical classification system for the early diagnosis of most common fetal pathologies.

Detection of fetal electrocardiogram signals using matched filters with adaptive normalisation

The authors discuss the application of matched litters to the detection of R-waves in fetal electrocardiogram (FECG) data, recorded during labour using a scalp electrode. When using the basic matched filter, one correlates a template representing the clean signal with the noisy signal. This method is optimal when the underlying noise is white in nature. However, it is known that false detection of R-waves can occur in the presence of extraneous peaks which have a similar shape to the fetal R-wave. It is proposed to switch between two different normalisations of the impulse response of the matched filter to alleviate this problem. When the signal-to-noise ratio is lower than a predetermined threshold, then normalisation to the geometric mean of the template and noisy data energies is carried out, otherwise only normalisation to the template energy is made. In the former case, the background noise and spikes that are larger than the underlying FECG are attenuated, hence increasing the probability of detection of the R-waves. In the latter case, noise, which has a lower amplitude than the underlying R-wave, is reduced. The effectiveness of this method is demonstrated by application to scalp electrode data.

Developments in CTG analysis

FHR monitoring has been the subject of many debates. The technique, in itself, can be considered to be accurate and reliable both in the antenatal period, when using the Doppler signal in combination with autocorrelation techniques, and during the intrapartum period, in particular when the FHR signal can be obtained from a fetal ECG electrode placed on the presenting part. The major problems with FHR monitoring relate to the reading and interpretation of the CTG tracings. Since the FHR pattern is primarily an expression of the activity of the control by the central and peripheral nervous system over cardiovascular haemodynamics, it is possibly too indirect a signal. In other specialities such as neonatology, anaesthesiology and cardiology, monitoring and graphic display of heart rate patterns have not gained wide acceptance among clinicians. Digitized archiving, numerical analysis and even more advanced techniques, as described in this chapter, have primarily found a place in obstetrics. This can be easily explained, since the obstetrician is fully dependent on indirectly collected information regarding the fetal condition, such as (a) movements experienced by the mother, observed with ultrasound or recorded with kinetocardiotocography (Schmidt, 1994), (b) perfusion of various vessels, as assessed by Doppler velocimetry, (c) the amount of amniotic fluid or (d) changes reflected in the condition of the mother, such as the development of gestation-induced hypertension and (e) the easily, continuously obtainable FHR signal. It is of particular comfort to the obstetrician that a normal FHR tracing reliably predicts the birth of the infant in a good condition, which makes cardiotocography so attractive for widespread application. However, in the intrapartum period, many traces cannot fulfil the criteria of normality, especially in the second stage. In this respect, cardiotocography remains primarily a screening and not so much a diagnostic method. As long as continuous monitoring of fetal acid-base balance has not been extensively tested in clinical practice, microblood sampling of the fetal presenting part (Saling, 1994) is a useful adjunct. The problem with non-normal tracings is that their significance is very often unclear. They may indicate serious fetal distress, finally resulting in preventable destruction of critical areas in the fetal brain and damage to various organs; or, on the contrary, they may indicate temporary changes in cardiovascular control as a reaction to the intermittent effects on fetal haemodynamics of, for example, uterine contractions, whether or not in combination with partial or complete compression of umbilical cord vessels or the vessels on the chorionic plate (van Geijn, 1994). Many factors influence the FHR and its variability, which further complicates the interpretation of FHR patterns; some have been discussed here in some detail. Undoubtedly, there is a need for quantitative and objective FHR analysis, as long as it does not lead to erroneous results. Close collaboration between engineers and clinicians is a prerequisite for further advances in this field. Decision support systems certainly have a future but only if they are able to take into account a large set of clinical data and can combine it with data obtained from FHR signals and other parameters referring to the fetal condition, such as fetal growth, Doppler velocimetry, amniotic fluid volume and biochemical and biophysical data obtained from the mother. Basic technical concepts inherent in computerized CTG analysis, such as sampling rate (Chang et al, 1995), signal loss, artefact detection (van Geijn et al, 1980), further processing of intervals, archiving in digitized format and monitor display, should receive considerable attention. There is still a long way to go until decision support systems find their way into obstetric practice. Further developments can only be achieved thanks to efforts of many basic and clinical researchers, wo

Power spectral analysis of the foetal magnetocardiogram

The results of power spectral analysis of foetal magnetocardiographic (FMCG) data, acquired using a DC-SQUID-based system, are reported. Similar analyses have been previously reported using foetal electrocardiographic data, but it is believed that our work represents one of the first attempts to analyse, in the frequency domain, the magnetic fields produced by foetal cardiac activity. Analysis of the data in this way may enable the integrity of the foetal nervous system, and thus the status of the foetus as a whole, to be monitored and evaluated during a significant part of the antenatal period. The results obtained are discussed with reference to the probable underlying physiological mechanisms. This preliminary study highlights some of the advantages of FMCG as a novel, non-invasive technique for obtaining clinically useful information. Fourier analysis of the FMCG data is likely to yield new information, not only about cardiac function but also about the foetal central nervous system.

Spectral analysis of fetal heart rate in flat recordings

Flat heart rate recordings may be observed in different fetal states such as chronic distress and sleep. Their visual analysis do not allow the distinction between these two states. We used spectral analysis to study the heart rate patterns in 25 fetuses. Two significant (P < 5 x 10(-5)) groups were apparent from the determination of the position of the maximum energy peak (PMEP) in the high-frequency band (0.20-0.50 Hz): a PMEP at about 0.20 Hz (group 1), and another around 0.30 Hz (group 2). The two groups did not differ in spectral density (SD). The outcome of neonates showed that group 1 fetuses made good progress and produced healthy neonates; whereas group 2 comprised cases of chronic fetal distress, or even death in utero, and neonatal distress. The significance of this difference in PMEP between fetal heart rate patterns in chronic distress and sleep is unclear. Studies combining the assessment of fetal movements and the determination of PMEP are planned.

Power spectral analysis of fetal heart rate

This chapter examines the role of power spectral analysis (PSA) in elucidation of the physiological control mechanisms of fetal heart rate and as a potential indicator of fetal well-being. The importance of fetal heart rate variability (FHRV) as an indicator of fetal oxygenation is discussed, and the limitations in the current methods of measurement of FHRV are highlighted. Evidence is presented for the paramount influence of the autonomic nervous system in the control of heart rate variability. The basic proposition underlying spectral analysis is that the two autonomic branches influence heart rate in a frequency-dependent way, and their differential effects can be determined by PSA which breaks down the heart rate trace into its component frequencies. The application of PSA to heart rate variability data is an established tool in cardiology, and the published literature related to its use in the adult, neonate and fetus is reviewed. The power spectrum is sensitive to the activity state of the fetus, particularly fetal breathing movements, which have a variable effect on short- and long-term FHRV. There are a variety of mathematical approaches to the construction of power spectra, and a particular method of data acquisition and analysis is presented together with some theoretical background. Recent experimental evidence indicates a role for PSA as an indicator of fetal activity state, and the effect of hypoxia on the spectrum of the fetus in labour is discussed. There are some problems with the technique of PSA, particularly in regard to accepted definitions and methods of analysis. It is a powerful non-invasive tool in the elucidation of fetal cardiac control, but its value in the detection of the compromised fetus has yet to be tested in a clinical trial.

Quantification of the fetal heart rate variability by spectral analysis of fetal well-being and fetal distress

Our objectives were to increase the discrimination between fetal distress and fetal well-being, using fetal heart rate spectral analysis. Monitoring of the heart rate from 259 fetuses was done between 26 and 42 weeks, interpreted with classical criteria, and analysed with the spectral analysis method we developed. The fetal heart rate spectrum analysis performed on these recordings allow discrimination of fetal distress from the normal state using the energy value and frequency of the maximal energy in the high frequency band. We can conclude that the spectral analysis produces two significant parameters which could contribute to a multivariate approach to assessments of the physiological mechanisms of heart rate variability.

Fractal analysis of foetal heart rate variability

Current methods for analysing foetal heart rate (FHR) patterns have yet to meet their full potential in the recognition of hypoxia in the foetus. Following the recent suggestion that fractal analysis can be applied to FHR recordings, the current paper describes a method for distinguishing two simultaneous fractal dimensions in FHR variation. An irregular line was plotted from 2500 consecutive foetal heart beat to beat intervals derived from an ultrasound source. A window of 500 intervals was moved along the line in steps of 20 intervals. At each step the Richardson technique was used to make estimates of the length of the line within the window using 40 different ruler lengths. When the estimates were plotted against the ruler lengths on log-log axes the resulting curve exhibited two distinct linear regions, each demonstrating an inverse power relationship. From the two slopes the fractal dimensions were derived for unspecified low- and high-frequency FHR variation in the current window. The values of both fractal dimensions were plotted simultaneously with the irregular FHR line and were found to accord with perceived changes in FHR variation. The method described is simply a measure of the irregularity in a series of foetal heart beat to beat intervals: the existence of fractal properties in the irregular line does not of itself imply underlying deterministic dynamics (e.g. chaos). This new method of observing FHR variability requires no preprocessing of the measured data, which are all taken into account. Not only does it represent a method for studying normal foetal behaviour but also has potential as a sensitive indicator of impending foetal compromise.