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.

A Fixed-Lag Kalman Smoother to Filter Power Line Interference in Electrocardiogram Recordings.

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.

Cognitive deterioration in adult epilepsy: clinical characteristics of "Accelerated Cognitive Ageing".

OBJECTIVES: "Epileptic dementia" is reported in adults with childhood-onset refractory epilepsy. Cognitive deterioration can also occur in a "second-hit model". MATERIALS AND METHODS: We studied the clinical and neuropsychological characteristics of patients with cognitive deterioration (≥1 SD discrepancy between current IQ and premorbid IQ). Memory function, reaction time and processing speed were also evaluated. Analyses were performed to investigate which clinical characteristics correlated with cognitive deterioration. RESULTS: Twenty-seven patients were included with a mean age of 55.7 years old, an average age at epilepsy onset of 33.9 years and a mean duration of 21.8 years. Over 40% had experienced at least one status epilepticus. About 77.8% had at least one comorbid disease (most of (cardio)vascular origin). Cognitive deterioration scores were significant for both Performance IQ and Full Scale IQ, but not for Verbal IQ. Impairments in fluid functions primarily affected the IQ-scores. Memory was not impaired. Epilepsy factors explained 7% of the variance in deterioration, whereas 38% was explained by relatively low premorbid IQ and educational level, high age at seizure onset and older age. CONCLUSIONS: A subgroup of patients with localization-related epilepsy exhibits cognitive decline characterized by deterioration in PIQ and FSIQ, but with preserved higher order functions (VIQ and memory). Patients typically have epilepsia tarda, comorbid pathology, relatively low educational level and older age. These are factors known to increase the vulnerability of the brain by diminishing cognitive reserve. Cognitive deterioration may develop according to a stepwise "second-hit model", affecting and accelerating the cognitive ageing process.

Technical aspects of neurostimulation: Focus on equipment, electric field modeling, and stimulation protocols.

Neuromodulation is a field of science, medicine, and bioengineering that encompasses implantable and non-implantable technologies for the purpose of improving quality of life and functioning of humans. Brain neuromodulation involves different neurostimulation techniques: transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), vagus nerve stimulation (VNS), and deep brain stimulation (DBS), which are being used both to study their effects on cognitive brain functions and to treat neuropsychiatric disorders. The mechanisms of action of neurostimulation remain incompletely understood. Insight into the technical basis of neurostimulation might be a first step towards a more profound understanding of these mechanisms, which might lead to improved clinical outcome and therapeutic potential. This review provides an overview of the technical basis of neurostimulation focusing on the equipment, the present understanding of induced electric fields, and the stimulation protocols. The review is written from a technical perspective aimed at supporting the use of neurostimulation in clinical practice.

Cognitive deterioration in adult epilepsy: Does accelerated cognitive ageing exist?

A long-standing concern has been whether epilepsy contributes to cognitive decline or so-called 'epileptic dementia'. Although global cognitive decline is generally reported in the context of chronic refractory epilepsy, it is largely unknown what percentage of patients is at risk for decline. This review is focused on the identification of risk factors and characterization of aberrant cognitive trajectories in epilepsy. Evidence is found that the cognitive trajectory of patients with epilepsy over time differs from processes of cognitive ageing in healthy people, especially in adulthood-onset epilepsy. Cognitive deterioration in these patients seems to develop in a 'second hit model' and occurs when epilepsy hits on a brain that is already vulnerable or vice versa when comorbid problems develop in a person with epilepsy. Processes of ageing may be accelerated due to loss of brain plasticity and cognitive reserve capacity for which we coin the term 'accelerated cognitive ageing'. We believe that the concept of accelerated cognitive ageing can be helpful in providing a framework understanding global cognitive deterioration in epilepsy.

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).

Feasibility Study of a New Method for Low-Complexity Fetal Movement Detection From Abdominal ECG Recordings.

Fetal movement counting can provide valuable information on the fetal health, as a strong decrease in the number of movements can be seen as a precursor to fetal death. Typically, assessment of fetal health by fetal movement counting relies on the maternal perception of fetal activity. The percentage of detected movements is strongly subject dependent and with undivided attention of the mother varies between 37% and 88%. Various methods to assist in fetal movement detection exist based on a wide spectrum of measurement techniques. However, these are unsuitable for ambulatory or long-term observation. In this paper, a novel low-complexity method for fetal movement detection is presented based on amplitude and shape changes in the abdominally recorded fetal ECG. This method was compared to a state-of-the-art method from the literature. Using ultrasound-based movement annotations as ground truth, the presented method outperforms the state-of-the-art abdominal-ECG based method, with a sensitivity, specificity, and accuracy of 56%, 68%, and 63%, respectively. Additionally, a significant reduction in algorithm complexity is achieved, possibly enabling continuous ambulatory fetal movement detection and early detection of reduced fetal motility.

Selective heart rate variability analysis to account for uterine activity during labor and improve classification of fetal distress.

Cardiotocography (CTG) is currently the most often used technique for detection of fetal distress. Unfortunately, CTG has a poor specificity. Recent studies suggest that, in addition to CTG, information on fetal distress can be obtained from analysis of fetal heart rate variability (HRV). However, uterine contractions can strongly influence fetal HRV. The aim of this study is therefore to investigate whether HRV analysis for detection of fetal distress can be improved by distinguishing contractions from rest periods. Our results from feature selection indicate that HRV features calculated separately during contractions or during rest periods are more informative on fetal distress than HRV features that are calculated over the entire fetal heart rate. Furthermore, classification performance improved from a geometric mean of 69.0% to 79.6% when including the contraction-dependent HRV features, in addition to HRV features calculated over the entire fetal heart rate.

Motion artifacts in capacitive ECG measurements: reducing the combined effect of DC voltages and capacitance changes using an injection signal.

Capacitive electrodes are a promising alternative to the conventional adhesive electrodes for ECG measurements. They provide more comfort to the patient when integrated in everyday objects (e.g., beds or seats) for long-term monitoring. However, the application of capacitive sensors is limited by their high sensitivity to motion artifacts. For example, motion at the body-electrode interface causes variations of the coupling capacitance which, in the presence of a dc voltage across the coupling capacitor, create strong artifacts in the measurements. The origin, relevance, and reduction of this specific and important type of artifacts are studied here. An injection signal is exploited to track the variations of the coupling capacitance in real time. This information is then used by an identification scheme to estimate the artifacts and subtract them from the measurements. The method was evaluated in simulations, lab environments, and in a real-life recording on an adult's chest. For the type of artifact under study, a strong artifact reduction ranging from 40 dB for simulated data to 9 dB for a given real-life recording was achieved. The proposed method is automated, does not require any knowledge about the measurement system parameters, and provides an online estimate for the dc voltage across the coupling capacitor.

Unobtrusive ECG monitoring in the NICU using a capacitive sensing array.

The thin skin of preterm babies is easily damaged by adhesive electrodes, tapes, chest drains and needle-marks. The scars caused could be disfiguring or disabling to 10% of preterm newborns. Capacitive sensors present an attractive option for pervasively monitoring neonatal ECG, and can be embedded in a support system or even a garment worn by the neonate. This could improve comfort and reduce pain aiding better recovery as well as avoiding the scars caused by adhesive electrodes. In this work, we investigate the use of an array of capacitive sensors unobtrusively embedded in a mattress and used in a clinical environment for 15 preterm neonates. We also describe the analysis framework including the fusion of information from all sensors to provide a more accurate ECG signal. We propose a channel selection strategy as well as a method using physiological information to obtain a reliable ECG signal. When sensor coverage is well attained, results for both instantaneous heart rate and ECG signal shape analysis are very encouraging. The study also provides several insights on important factors affecting the results. These include the effect of textile type, number of layers, interferences (e.g. people walking by), motion severity and interventions. Incorporating this knowledge in the design of a capacitive sensing system would be crucial in ensuring that these sensors provide a reliable ECG signal when embedded in a neonatal support system.

Influence of electrode placement on signal quality for ambulatory pregnancy monitoring.

Noninvasive fetal health monitoring during pregnancy has become increasingly important in order to prevent complications, such as fetal hypoxia and preterm labor. With recent advances in signal processing technology using abdominal electrocardiogram (ECG) recordings, ambulatory fetal monitoring throughout pregnancy is now an important step closer to becoming feasible. The large number of electrodes required in current noise-robust solutions, however, leads to high power consumption and reduced patient comfort. In this paper, requirements for reliable fetal monitoring using a minimal number of electrodes are determined based on simulations and measurement results. To this end, a dipole-based model is proposed to simulate different electrode positions based on standard recordings. Results show a significant influence of bipolar lead orientation on maternal and fetal ECG measurement quality, as well as a significant influence of interelectrode distance for all signals of interest.

Fetal movement detection based on QRS amplitude variations in abdominal ECG recordings.

Evaluation of fetal motility can give insight in fetal health, as a strong decrease can be seen as a precursor to fetal death. Typically, the assessment of fetal health by fetal movement detection relies on the maternal perception of fetal activity. The percentage of detected movements is strongly subject dependent and with undivided attention of the mother varies between 37% to 88%. Various methods to assist in fetal movement detection exist based on a wide spectrum of measurement techniques. However, these are typically unsuitable for ambulatory or long-term observation. In this paper, a novel method for fetal motion detection is presented based on amplitude and shape changes in the abdominally recorded fetal ECG. The proposed method has a sensitivity and specificity of 0.67 and 0.90, respectively, outperforming alternative fetal ECG-based methods from the literature.

ECG reconstruction based on the injection of a multi-frequency signal in capacitive measurement systems.

Many healthcare and lifestyle applications could benefit from capacitive measurement systems for unobtrusive ECG monitoring. However, a key technical challenge remains: the susceptibility of such systems to motion artifacts and common-mode interferences. With this in mind, we developed a novel method to reduce various types of artifacts present in capacitive ECG measurement systems. The objective is to perform ECG reconstruction and channel balancing in an automated and continuous manner. The proposed method consists of a) modeling the measurement system; b) specifically parameterizing the reconstruction equation; and c) adaptively estimating the parameters. A multi-frequency injection signal serves to estimate and track the variations of the different parameters of the reconstruction equation. A preliminary investigation on the validity of the method has been performed in both simulation and lab environment: the method shows benefits in terms of common-mode interference and motion artifact reduction, resulting in improved R-peak detection.

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.

Laser-speckle-based detection of fluid pulsation in the presence of motion artifacts: in vitro and in vivo study.

We have performed an in vitro and in vivo study, based on laser speckle contrast analysis, to detect fluid pulsation in the presence of artifacts caused by the relative motion between the sample and the illumination source. We observe that the pulsation signal is clearly detectable for a range of motion amplitudes and oscillation frequencies; however, for higher amplitudes and oscillation frequencies of motion, the signal, due to pulsation, becomes increasingly difficult to detect.

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.

A robust physiology-based source separation method for QRS detection in low amplitude fetal ECG recordings.

The use of the non-invasively obtained fetal electrocardiogram (ECG) in fetal monitoring is complicated by the low signal-to-noise ratio (SNR) of ECG signals. Even after removal of the predominant interference (i.e. the maternal ECG), the SNR is generally too low for medical diagnostics, and hence additional signal processing is still required. To this end, several methods for exploiting the spatial correlation of multi-channel fetal ECG recordings from the maternal abdomen have been proposed in the literature, of which principal component analysis (PCA) and independent component analysis (ICA) are the most prominent. Both PCA and ICA, however, suffer from the drawback that they are blind source separation (BSS) techniques and as such suboptimum in that they do not consider a priori knowledge on the abdominal electrode configuration and fetal heart activity. In this paper we propose a source separation technique that is based on the physiology of the fetal heart and on the knowledge of the electrode configuration. This technique operates by calculating the spatial fetal vectorcardiogram (VCG) and approximating the VCG for several overlayed heartbeats by an ellipse. By subsequently projecting the VCG onto the long axis of this ellipse, a source signal of the fetal ECG can be obtained. To evaluate the developed technique, its performance is compared to that of both PCA and ICA and to that of augmented versions of these techniques (aPCA and aICA; PCA and ICA applied on preprocessed signals) in generating a fetal ECG source signal with enhanced SNR that can be used to detect fetal QRS complexes. The evaluation shows that the developed source separation technique performs slightly better than aPCA and aICA and outperforms PCA and ICA and has the main advantage that, with respect to aPCA/PCA and aICA/ICA, it performs more robustly. This advantage renders it favorable for employment in automated, real-time fetal monitoring applications.

Fetal autonomic response to severe acidaemia during labour.

OBJECTIVE: Spectral analysis of heart-rate variability is used to monitor autonomic nervous system fluctuations. The low-frequency component is associated with sympathetic and parasympathetic modulation and the high-frequency component is associated with parasympathetic modulation. The objective was to study whether changes in low-frequency or high-frequency power of heart-rate variability occur in case of fetal distress. DESIGN: Case-control study. SETTING: Obstetric unit of a tertiary-care teaching hospital. POPULATION: Twenty healthy human fetuses during labour at term of which ten had an umbilical artery pH < 7.05 (cases), and ten had an arterial pH > 7.20 (controls) after birth. METHODS: Spectral information about fetal beat-to-beat heart rate, calculated from direct fetal electrocardiogram registrations, was obtained by using a short-time Fourier transform. MAIN OUTCOME MEASURES: Absolute power and normalised power in the low-frequency and high-frequency bands. RESULTS: No differences were found between fetuses with and without acidaemia in absolute low or high frequency power (P = 0.2 and P = 0.3, respectively). During the last 30 minutes of labour, acidaemic fetuses had significantly increased normalised low-frequency power (P = 0.01) and decreased normalised high-frequency power (P = 0.03) compared with non-acidaemic fetuses. These differences were not observed from 3 to 2 hours before birth (P = 0.7 and P = 0.9, respectively). CONCLUSION: The autonomic nervous system of human fetuses at term responds adequately to severe stress during labour. Normalised low and high frequency power of heart-rate variability might be able to discriminate between normal and abnormal fetal condition.

Myometrium electromechanical modeling for internal uterine pressure estimation by electrohysterography.

During delivery, quantitative information on the uterine activity can be provided by internal uterine pressure (IUP) recordings using an invasive intrauterine pressure catheter (IUPC). The electrohysterogram, which measures the electrical signal that drives the mechanical contraction of the uterine muscle and the consequent IUP increase, is recorded by electrodes placed on the abdomen. Recent work demonstrated the possibility of reliably estimating the IUP noninvasively by electrohysterographic (EHG) signal analysis. To further improve the accuracy of IUP estimates, we investigated the use of three nonlinear functions for modeling the relationship between the electrical activation measured by the EHG signal and the mechanical response of the uterine muscle. The feature employed for obtaining a first estimate of the IUP is the unnormalized first statistical moment of the EHG spectrum. The relationship between the extracted feature and the IUP is modeled by a second-order polynomial, a logarithmic, and an exponential function. For validation, the IUPC and the EHG signals were recorded on nine women in labor. A second-order polynomial model already provided estimates that are highly correlated with the IUPC signal (r = 0.73). However, the logarithmic model resulted to be the most accurate, especially in terms of root mean squared error (RMSE = 5.13 mmHg).

Electrohysterographic conduction velocity estimation.

Monitoring and analysis of the fetal-heart and the uterine-muscle activity, referred to as electrohysterogram (EHG), is essential to permit timely treatment during pregnancy. While remarkable progress is reported for monitoring of the fetal cardiac activity, the EHG measurement and interpretation remains challenging, and limited knowledge is available on the underlying physiological processes. In particular, little attention has been paid to the analysis of the EHG propagation, whose characteristics might indicate the presence of coordinated uterine contractions leading to intrauterine pressure increase. Therefore, this study focuses for the first time on the noninvasive estimation of the conduction velocity of EHG action potentials by means of multichannel EHG recording and surface high-density electrodes. A maximum likelihood algorithm, initially proposed for skeletal-muscle electromyog-raphy, is modified for the required EHG analysis. The use of clustering and weighting is introduced to deal with poor signal similarity between different channels. The presented methods were evaluated by specific simulations, proving the combination of weighting and clustering to be the most accurate method. A preliminary EHG measurement during labor confirmed the feasibility of the method. An extensive clinical validation will however be necessary to optimize the method and assess the relevance of the EHG conduction velocity for pregnancy monitoring.