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Aim Out-of-hospital cardiac arrest is a major health problem, and the overall survival rate is low (4.6%–16.4%). The initiation of the current chain of survival depends on the presence of a witness of the cardiac arrest, which is not present in 29.7%–63.4% of the cases. Furthermore, a delay in starting this chain is common in witnessed out-of-hospital cardiac arrest. This project aims to reduce morbidity and mortality due to out-of-hospital cardiac arrest by developing a smartwatch-based solution to expedite the chain of survival in the case of (un)witnessed out-of-hospital cardiac arrest. Methods Within the ‘Beating Cardiac Arrest’ project, we aim to develop a demonstrator product that detects out-of-hospital cardiac arrest using photoplethysmography and accelerometer analysis, and autonomously alerts emergency medical services. A target group study will be performed to determine who benefits the most from this product. Furthermore, several clinical studies will be conducted to capture or simulate data on out-of-hospital cardiac arrest cases, as to develop detection algorithms and validate their diagnostic performance. For this, the product will be worn by patients at high risk for out-of-hospital cardiac arrest, by volunteers who will temporarily interrupt blood flow in their arm by inflating a blood pressure cuff, and by patients who undergo cardiac electrophysiologic and implantable cardioverter defibrillator testing procedures. Moreover, studies on psychosocial and ethical acceptability will be conducted, consisting of surveys, focus groups, and interviews. These studies will focus on end-user preferences and needs, to ensure that important individual and societal values are respected in the design process.

Due to the association between dysfunctional maternal autonomic regulation and pregnancy complications, tracking non-invasive features of autonomic regulation derived from wrist-worn photoplethysmography (PPG) measurements may allow for the early detection of deteriorations in maternal health. However, even though a plethora of these features-specifically, features describing heart rate variability (HRV) and the morphology of the PPG waveform (morphological features)-exist in the literature, it is unclear which of these may be valuable for tracking maternal health. As an initial step towards clarity, we compute comprehensive sets of HRV and morphological features from nighttime PPG measurements. From these, using logistic regression and stepwise forward feature elimination, we identify the features that best differentiate healthy pregnant women from non-pregnant women, since these likely capture physiological adaptations necessary for sustaining healthy pregnancy. Overall, morphological features were more valuable for discriminating between pregnant and non-pregnant women than HRV features (area under the receiver operating characteristics curve of 0.825 and 0.74, respectively), with the systolic pulse wave deterioration being the most valuable single feature, followed by mean heart rate (HR). Additionally, we stratified the analysis by sleep stages and found that using features calculated only from periods of deep sleep enhanced the differences between the two groups. In conclusion, we postulate that in addition to HRV features, morphological features may also be useful in tracking maternal health and suggest specific features to be included in future research concerning maternal health.

Objective. Appropriate adaptation of the maternal autonomic nervous system to progressing gestation is essential to a healthy pregnancy. This is partly evidenced by the association between pregnancy complications and autonomic dysfunction. Therefore, assessing maternal heart rate variability (HRV)—a proxy measure for autonomic activity—may offer insights into maternal health, potentially enabling the early detection of complications. However, identifying abnormal maternal HRV requires a thorough understanding of normal maternal HRV. While HRV in women of childbearing age has been extensively investigated, less is known concerning HRV during pregnancy. Subsequently, we investigate the differences in HRV between healthy pregnant women and their non-pregnant counterparts. Approach. We use a comprehensive suite of HRV features (assessing sympathetic and parasympathetic activity, heart rate (HR) complexity, HR fragmentation, and autonomic responsiveness) to quantify HRV in large groups of healthy pregnant (n = 258) and non-pregnant women (n = 252). We compare the statistical significance and effect size of the potential differences between the groups. Main results. We find significantly increased sympathetic and decreased parasympathetic activity during healthy pregnancy, along with significantly attenuated autonomic responsiveness, which we hypothesize serves as a protective mechanism against sympathetic overactivity. HRV differences between these groups typically had a large effect size (Cohen’s d > 0.8), with the largest effect accompanying the significantly reduced HR complexity and altered sympathovagal balance observed in pregnancy (Cohen’s d > 1.2). Significance. Healthy pregnant women are autonomically distinct from their non-pregnant counterparts. Subsequently, assumptions based on HRV research in non-pregnant women cannot be readily translated to pregnant women.

BACKGROUND: The diagnostic value of ST analysis of the fetal electrocardiogram (fECG) during labor is uncertain. False alarms (ST events) may be explained by physiological variation of the fetal electrical heart axis. Adjusted ST events, based on a relative rather than an absolute rise from baseline, correct for this variation and may improve the diagnostic accuracy of ST analysis.AIMS: Determine the optimal cut-off for relative ST events in fECG to detect fetal metabolic acidosis.STUDY DESIGN: Post-hoc analysis on fECG tracings from the Dutch STAN trial (STAN+CTG branch).SUBJECTS: 1328 term singleton fetuses with scalp ECG tracing during labor, including 10 cases of metabolic acidosis.OUTCOME MEASURES: Cut-off value for relative ST events at the point closest to (0,1) in the receiver operating characteristic (ROC) curve with corresponding sensitivity and specificity.RESULTS: Relative baseline ST events had an optimal cut-off at an increment of 85% from baseline. Relative ST events had a sensitivity of 90% and specificity of 80%.CONCLUSIONS: Adjusting the current definition of ST events may improve ST analysis, making it independent of CTG interpretation.

Contains fulltext : 220481.pdf (publisher's version ) (Open Access), INTRODUCTION: The examination of the fetal heart in mid-pregnancy is by ultrasound examination. The quality of the examination is highly dependent on the skill of the sonographer, fetal position and maternal body mass index. An additional tool that is less dependent on human experience and interpretation is desirable. The fetal electrocardiogram (ECG) could fulfill this purpose. We aimed to show the feasibility of recording a standardized fetal ECG in mid-pregnancy and explored its possibility to detect congenital heart disease (CHD). MATERIALS AND METHODS: Women older than 18 years of age with an uneventful pregnancy, carrying a healthy singleton fetus with a gestational age between 18 and 24 weeks were included. A fetal ECG was performed via electrodes on the maternal abdomen. After removal of interferences, a vectorcardiogram was constructed. Based on the ultrasound assessment of the fetal orientation, the vectorcardiogram was rotated to standardize for fetal orientation and converted into a 12-lead ECG. Median ECG waveforms for each lead were calculated. RESULTS: 328 fetal ECGs were recorded. 281 were available for analysis. The calculated median ECG waveform showed the electrical heart axis oriented to the right and inferiorly i.e. a negative QRS deflection in lead I and a positive deflection in lead aVF. The two CHD cases show ECG abnormalities when compared to the mean ECG of the healthy cohort. DISCUSSION: We have presented a method for estimating a standardized 12-lead fetal ECG. In mid-pregnancy, the median electrical heart axis is right inferiorly oriented in healthy fetuses. Future research should focus on fetuses with congenital heart disease.

Contains fulltext : 215804.pdf (publisher's version ) (Open Access), BACKGROUND: Fetal monitoring based on electrocardiographic (ECG) morphology is obtained from a single unipolar fetal scalp electrode. Ideally, it should be obtained from multiple leads, as ECG waveform depends on alignment between electrode and electrical heart axis. This alignment is unknown in fetuses. Besides, fetuses are surrounded by conductive media, which may influence ECG waveform. We explored the influence of electrode position and head orientation on ECG waveforms of unipolar and bipolar scalp ECGs recorded in air and in conductive medium. METHODS: We recorded ECGs in one adult subject at five different scalp positions in five different head orientations both in dry and immersed conditions. The ratio between T-amplitude and QRS-amplitude (T/QRS ratio) of unipolar and bipolar scalp ECGs was determined and compared between all conditions. RESULTS: In the dry condition, we observed in the unipolar leads little to no difference between different electrode positions (maximal T/QRS difference 0.00-0.01) and minor differences between head orientations (0.02-0.03), whereas bipolar leads showed no recognizable ECG signal at all. During the immersed condition, we found variation in the unipolar leads, both between electrode positions (maximal T/QRS difference 0.02-0.05) and between head orientations (0.03-0.06). Bipolar leads showed different ECG signals in contrasting head orientations. CONCLUSIONS: Both unipolar and bipolar scalp lead-derived ECG waveforms are influenced by electrode position and head orientation when the subject is submerged in a conductive medium. Fetal monitoring based on single scalp lead ECG waveform might be suboptimal, as it lacks correction for fetal head orientation and electrode position.

Item does not contain fulltext, 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.

Contains fulltext : 199942.pdf (publisher's version ) (Closed access), Autonomic cardiac activity during sleep has been widely studied. Research has mostly focused on cardiac activity between different sleep stages and wakefulness as well as between normal and pathological sleep. This work investigates autonomic activity changes during sleep onset in healthy subjects with long and short sleep onset latency (SOL). Polysomnography (PSG) and electrocardiography (ECG) were simultaneously recorded in 186 healthy subjects during a single night. Autonomic activity was assessed based on frequency domain analysis of RR intervals and results show that the analysis of RR intervals differs significantly between the short SOL and the long SOL groups. We found that the spectral power in the low frequency band (LF) was significantly higher in the long SOL group compared to the short SOL group in the first 10 minutes in bed intended to sleep. There was no significant difference for LF and the spectral power in the high frequency band (HF) 10 minutes before and after sleep onset between the two groups. Only in the short SOL group there was a significant increase in HF from the first 10 minutes in bed intended to sleep to 10 minutes before SO, while LF decreased significantly in both groups. The effect of time (5.5-min bin) on the heart rate variability (HRV) features around sleep onset showed that both LF and HF differed significantly during the period surrounding sleep onset only in the short SOL group.

Contains fulltext : 200282.pdf (publisher's version ) (Closed access), Obstructive sleep apnea syndrome (OSAS) is a sleep disorder that affects a large part of the population and the development of algorithms using cardiovascular features for OSAS monitoring has been an extensively researched topic in the last two decades. Several studies regarding automatic apneic event classification using ECG derived features are based on the public Apnea-ECG database available on PhysioNet. Although this database is an excellent starting point for apnea topic investigations, in our study we show that algorithms for apneic-epochs classification that are successfully trained on this database (sensitivity < 85%, false detection rate <20%) perform poorly (sensitivity\textit<55%, false detection rate < 40%) in other databases which include patients with a broader spectrum of apneic events and sleep disorders. The reduced performance can be related to the complexity of breathing events, the increased number of non-breathing related sleep events, and the presence of non-OSAS sleep pathologies.

Item does not contain fulltext, 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.

Item does not contain fulltext, 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 24weeks 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.

Obstructive sleep apnea syndrome (OSAS) is a sleep disorder that affects a large part of the population and the development of algorithms using cardiovascular features for OSAS monitoring has been an extensively researched topic in the last two decades. Several studies regarding automatic apneic event classification using ECG derived features are based on the public Apnea-ECG database available on PhysioNet. Although this database is an excellent starting point for apnea topic investigations, in our study we show that algorithms for apneic-epochs classification that are successfully trained on this database (sensitivity < 85%, false detection rate <20%) perform poorly (sensitivity\textit<55%, false detection rate < 40%) in other databases which include patients with a broader spectrum of apneic events and sleep disorders. The reduced performance can be related to the complexity of breathing events, the increased number of non-breathing related sleep events, and the presence of non-OSAS sleep pathologies.

Contains fulltext : 182367.pdf (publisher's version ) (Closed access), Photoplethysmography (PPG) is one of the key technologies for unobtrusive physiological monitoring, with ongoing attempts to use it in several medical fields, ranging from night to night sleep analysis to continuous cardiac arrhythmia monitoring. However, the PPG signals are susceptible to be corrupted by noise and artifacts, caused, e.g., by limb or sensor movement. These artifacts affect the morphology of PPG waves and prevent the accurate detection and localization of beats and subsequent cardiovascular feature extraction. In this paper a new algorithm for beat detection and pulse quality assessment is described. The algorithm segments the PPG signal in pulses, localizes each beat and grades each segment with a quality index. The obtained index results from a comparison between each pulse and a template derived from the surrounding pulses, by mean of dynamic time warping barycenter averaging. The quality index is used to discard corrupted pulse beats. The algorithm is evaluated by comparing the detected beats with annotated PPG signals and the results are published over the same data. The described method achieves an improved sensitivity and a higher predictive value.

OBJECTIVE: Doppler ultrasound (US) is the most commonly applied method to measure the fetal heart rate (fHR). When the fetal heart is not properly located within the ultrasonic beam, fHR measurements often fail. As a consequence, clinical staff need to reposition the US transducer on the maternal abdomen, which can be a time consuming and tedious task.APPROACH: In this article, a method is presented to aid clinicians with the positioning of the US transducer to produce robust fHR measurements. A maximum likelihood estimation (MLE) algorithm is developed, which provides information on fetal heart location using the power of the Doppler signals received in the individual elements of a standard US transducer for fHR recordings. The performance of the algorithm is evaluated with simulations and in vitro experiments performed on a beating-heart setup.MAIN RESULTS: Both the experiments and the simulations show that the heart location can be accurately determined with an error of less than 7 mm within the measurement volume of the employed US transducer.SIGNIFICANCE: The results show that the developed algorithm can be used to provide accurate feedback on fetal heart location for improved positioning of the US transducer, which may lead to improved measurements of the fHR.

Background Insomnia disorder is a widespread sleep disorder with a prevalence of approximately 10%. Even though the link between insomnia and cardiovascular activity is not exactly clear, it is generally assumed that cardiovascular autonomic modifications could occur as a result of sleeplessness, or, alternatively, that autonomic alterations could be an expression of a hyper-arousal state. This review investigates whether cardiovascular measures are different between insomniacs and controls. Methods Electronic databases were systematically searched, and 34 studies were identified. Heart rate variability features, the association of cardiac and EEG activity, physiologic complexity measures, and cardiovascular activity, assessed by measures such as pre-ejection time, blood pressure, and heart rate dynamics were studied. Given the heterogeneity of the studies, a narrative synthesis of the findings was performed. Results This review study found overall differences in cardiovascular activity between insomniacs and controls in most of the observational studies (21/26), while the expression of cardiovascular regulation varied between the examined insomniac groups. All the studies that investigated the association of cardiac activity and EEG power reported an altered relation between autonomic activity and EEG parameters in insomniacs. Conclusion Autonomic regulation tends to be consistent between insomniacs, as long as they are grouped according to their respective phenotype, as shown in the insomnia subgroup with objectively short sleep duration. Our hypothesis is that these differences in the expression of cardiovascular activity could be explained by the heterogeneity of the disorder. Therefore, the determination of insomnia phenotypes, and the study of cardiovascular measures, rather than heart rate variability alone, will give more insight into the link between insomnia and cardiovascular regulation. This study suggests that cardiovas

Background: Coaches in elite swimming carefully design the training programs of their swimmers and are keen on achieving strict adherence to those programs by their athletes. At present, coaches usually monitor the compliance of their swimmers to the training program with a stopwatch. However, this measurement clearly limits the monitoring possibilities and is subject to human error. Therefore, the present study was designed to examine the reliability and practical usefulness of tri-axial accelerometers for monitoring lap time, stroke count and stroke rate in swimming. Methods: In the first part of the study, a 1200 m warm-up swimming routine was measured in 13 elite swimmers using tri-axial accelerometers and synchronized video recordings. Reliability was determined using the typical error of measurement (TEM) as well as a Bland-Altman analysis. In the second part, training compliance both within and between carefully prescribed training sessions was assessed in four swimmers in order to determine the practical usefulness of the adopted accelerometric approach. In these sessions, targets were set for lap time and stroke count by the coach. Results: The results indicated high reliability for lap time (TEM = 0.26 s, bias = 0.74 [0.56 0.91] with limits of agreement (LoA) from −1.20 [−1.50 −0.90] to 2.70 [2.40 3.00]), stroke count (TEM 0.73 strokes, bias = 0.46 [0.32 0.60] with LoA from −1.70 [−1.94 −1.46] to 2.60 [2.36 2.84]) and stroke rate (TEM 0.72 str∙min−1, bias = −0.13 [−0.20 −0.06] with LoA from −2.20 [−2.32 −2.08] to 1.90 [1.78 2.02]), while the results for the monitoring of training compliance demonstrated the practical usefulness of our approach in daily swimming training. Conclusions: The daily training of elite swimmers can be accurately and reliably monitored using tri-axial accelerometers. They provide the coach with more useful information to guide and control the training process than hand-clocked times. View Full-Text Keywords: training; mon

OBJECTIVE: Reducing perinatal morbidity and mortality is one of the major challenges in modern health care. Analysing the ST segment of the fetal electrocardiogram was thought to be the breakthrough in fetal monitoring during labour. However, its implementation in clinical practice yields many false alarms and ST monitoring is highly dependent on cardiotocogram assessment, limiting its value for the prediction of fetal distress during labour. This study aims to evaluate the relation between physiological variations in the orientation of the fetal electrical heart axis and the occurrence of ST events. METHODS: A post-hoc analysis was performed following a multicentre randomised controlled trial, including 1097 patients from two participating centres. All women were monitored with ST analysis during labour. Cases of fetal metabolic acidosis, poor signal quality, missing blood gas analysis, and congenital heart disease were excluded. The orientation of the fetal electrical heart axis affects the height of the initial T/QRS baseline, and therefore the incidence of ST events. We grouped tracings with the same initial baseline T/QRS value. We depicted the number of ST events as a function of the initial baseline T/QRS value with a linear regression model. RESULTS: A significant increment of ST events was observed with increasing height of the initial T/QRS baseline, irrespective of the fetal condition; correlation coefficient 0.63, p<0.001. The most frequent T/QRS baseline is 0.12. CONCLUSION: The orientation of the fetal electrical heart axis and accordingly the height of the initial T/QRS baseline should be taken into account in fetal monitoring with ST analysis.

In the last decades, photoplethysmography (PPG) has been employed in a wide spectrum of applications, ranging from consumer devices to medical equipment. The pulsatile PPG signal recorded contains valuable information on the cardio-vascular and -respiratory system. Several features can be derived from the PPG and these can be used to infer physiological states of the human system, for instance to estimate the sleep structure or the fitness level of a subject [1]. As every sensing technology, the PPG can be corrupted by artifacts so it needs to be enhanced and, sometimes, parts of it have to be rejected. The rejection becomes fundamental especially when features are based on the shape of the signal. In literature, several methods are available to determine a quality index (QI) of parts of the PPG and use this QI as criterion for segment rejection. However, these methods exclude entire segments of the signal rather than single pulses, or they calculate a QI susceptible to the physiological PPG variation. In this study, a new algorithm for single PPG pulse QI calculation is proposed. This QI ranges between 0 and 1 and it is assessed by comparing each pulse with a template. The template is derived from PPG by using dynamic time warping (DTW) barycenter averaging [2]. Each pulse is warped, using DTW, to maximize the match with the template and the QI is calculated as a normalized root mean square error of the remaining mismatch. The QI is resilient to physiological pulse deformations, but still able to quantify the pulse morphology corruption and to recognize artifacts. The algorithm is validated on the Complex System Laboratory database [3], according to the ANSI/AAMI standards. For each pulse the beat location is calculated and it is rejected if QI is lower than 0.5. The positive predictive value and sensitivity (PPV, SEN) are calculated with respect to human beat annotations, with a true positive detection criterion of 30 ms distance from the annotated beat. T

Objective: Filtering power line interference (PLI) from electrocardiogram (ECG) recordings can lead to significant distortions of the ECG and mask clinically relevant features in ECG waveform morphology. The objective of this study is to filter PLI from ECG recordings with minimal distortion of the ECG waveform. Methods: In this paper, we propose a fixed-lag Kalman smoother with adaptive noise estimation. The performance of this Kalman smoother in filtering PLI is compared to that of a fixed-bandwidth notch filter and several adaptive PLI filters that have been proposed in the literature. To evaluate the performance, we corrupted clean neonatal ECG recordings with various simulated PLI. Furthermore, examples are shown of filtering real PLI from an adult and a fetal ECG recording. Results: The fixed-lag Kalman smoother outperforms other PLI filters in terms of step response settling time (improvements that range from 0.1 to 1 s) and signal-to-noise ratio (improvements that range from 17 to 23 dB). Our fixed-lag Kalman smoother can be used for semi real-time applications with a limited delay of 0.4 s. Conclusion and Significance: The fixed-lag Kalman smoother presented in this study outperforms other methods for filtering PLI and leads to minimal distortion of the ECG waveform.

Background Congenital heart disease (CHD) is the most common severe congenital anomaly worldwide. Diagnosis early in pregnancy is important, but the detection rate by two-dimensional ultrasonography is only 65%–81%. Objectives To evaluate existing data on CHD and noninvasive abdominal fetal electrocardiography (ECG). Search strategy A systematic review was performed through a search of the Cochrane Library, PubMed, and Embase for studies published up to April 2016 using the terms “congenital heart disease,” “fetal electrocardiogram,” and other similar keywords. Selection criteria Primary articles that described changes in fetal ECG among fetuses with CHD published in English were included. Data collection and analysis Outcomes of interest were changes in fetal ECG parameters observed for fetuses with congenital heart disease. Findings were reported descriptively. Main results Only five studies described changes observed in the fetal electrocardiogram for fetuses with CHD, including heart rate, heart rate variability, and PR, QRS, and QT intervals. Fetal ECG reflects the intimate relationship between the cardiac nerve conduction system and the structural morphology of the heart. It seems particularly helpful in detecting the electrophysiological effects of cardiac anatomic defects (e.g. hypotrophy, hypertrophy, and conduction interruption). Conclusions Fetal ECG might be a promising clinical tool to complement ultrasonography in the screening program for CHD.

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).