C Chiara Rabotti

A robust fetal ECG detection method for abdominal recordings

In this paper, we propose a new method for FECG detection in abdominal recordings. The method consists of a sequential analysis approach, in which the a priori information about the interference signals is used for the detection of the FECG. Our method is evaluated on a set of 20 abdominal recordings from pregnant women with different gestational ages. Its performance in terms of fetal heart rate (FHR) detection success is compared with that of independent component analysis (ICA). The results show that our sequential estimation method outperforms ICA with a FHR detection rate of 85% versus 60% of ICA. The superior performance of our method is especially evident in recordings with a low signal-to-noise ratio (SNR). This indicates that our method is more robust than ICA for FECG detection.

Estimation of internal uterine pressure by joint amplitude and frequency analysis of electrohysterographic signals

Monitoring the uterine contraction provides important prognostic information during pregnancy and parturition. The existing methods employed in clinical practice impose a compromise between reliability and invasiveness. A promising technique for uterine contraction monitoring is electrohysterography (EHG). The EHG signal measures the electrical activity which triggers the contraction of the uterine muscle. In this paper, a non-invasive method for intrauterine pressure (IUP) estimation by EHG signal analysis is proposed. The EHG signal is regarded as a non-stationary signal whose frequency and amplitude characteristics are related to the IUP. After acquisition in a multi-channel configuration, the EHG signal is therefore analyzed in the time-frequency domain. A first estimation of the IUP is then derived by calculation of the unnormalized first statistical moment of the frequency spectrum. The estimation accuracy is finally increased by identification of a second-order polynomial model. The proposed method is compared to root mean squared analysis and optimal linear filtering and validated by simultaneous measurement of the IUP on nine women during labor. The results suggest that the proposed EHG signal analysis provides an accurate estimate of the IUP.

Noninvasive Estimation of the Electrohysterographic Action-Potential Conduction Velocity

Electrophysiological monitoring of the fetal-heart and the uterine-muscle activity, referred to as an electrohysterogram, is essential to permit timely treatment during pregnancy. While remarkable progress is reported for fetal-cardiac-activity monitoring, the electrohysterographic (EHG) measurement and interpretation remain challenging. In particular, little attention has been paid to the analysis of the EHG propagation, whose characteristics might be predictive of the preterm delivery. Therefore, this paper focuses, for the first time, on the noninvasive estimation of the conduction velocity of the EHG-action potentials. To this end, multichannel EHG recording and surface high-density electrodes are used. A maximum-likelihood method is employed for analyzing the EHG-action-potential propagation in two dimensions. The use of different weighting strategies of the derived cost function is introduced to deal with the poor signal similarity between different channels. The presented methods were evaluated by specific simulations proving the best weighting strategy to lead to an accuracy improvement of 56.7%. EHG measurements on ten women with uterine contractions confirmed the feasibility of the method by leading to conduction velocity values within the expected physiological range.

Accuracy of frequency-related parameters of the electrohysterogram for predicting preterm delivery: a review of the literature.

The diagnosis of labor and effective prevention of preterm delivery are still among the most significant problems faced by obstetricians. Currently, there is no technique or method for objectively monitoring the uterus and assessing whether the organ has entered a state of increased activity that may indicate labor. Several studies have investigated a new, noninvasive technique to monitor uterine contractions: the electrohysterogram (EHG). Analysis of frequency-related parameters of the EHG may allow physiological uterine activity to be distinguished from uterine contractions that will lead to preterm delivery. However, although a variety of parameters and methodologies have been employed, they have not been objectively compared. The objective of this review, which was based on a systematic literature search using the Cochrane, PubMed, and EMBASE databases up to February 2008, was to determine whether frequency-related parameters of the EHG signal can reliably differentiate preterm contractions that will lead to preterm delivery from those that will not (in patients who will ultimately deliver at term) and to identify the most accurate parameter. Of all the different EHG parameters, both human and animal studies indicate that the power spectral density peak frequency may be the most predictive of true labor. The best parameter for predicting delivery is, therefore, related to the EHG spectral content shift, as calculated by Fourier transform, time-frequency, or Wavelet analysis. The incidence and extent to which shifts in uterine electrical spectral components occur, as the measurement-to-delivery interval decreases, imply that these changes might be used to predict preterm delivery. There is also promising data suggesting that a combination of the measured parameters, used as inputs to artificial neural network algorithms, may be more useful than individual ones for critically assessing uterine activity. Target Audience: Obstetricians & Gynecologists, Family Physicians Learning Objectives: After completion of this article, the reader will be able to recall the physiology of uterine contractions leading to labor, summarize the limitations of tocodynamometry, and outline four different electrohysterogram parameters.

Low-complexity R-peak detection for ambulatory fetal monitoring

Non-invasive fetal health monitoring during pregnancy is becoming increasingly important because of the increasing number of high-risk pregnancies. Despite recent advances in signal-processing technology, which have enabled fetal monitoring during pregnancy using abdominal electrocardiogram (ECG) recordings, ubiquitous fetal health monitoring is still unfeasible due to the computational complexity of noise-robust solutions. In this paper, an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, without reducing the R-peak detection performance compared to the existing R-peak detection schemes. Validation of the algorithm is performed on three manually annotated datasets. With a detection error rate of 0.23%, 1.32% and 9.42% on the MIT/BIH Arrhythmia and in-house maternal and fetal databases, respectively, the detection rate of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.

A Low-Voltage Chopper-Stabilized Amplifier for Fetal ECG Monitoring With a 1.41 Power Efficiency Factor

This paper presents a low-voltage current-reuse chopper-stabilized frontend amplifier for fetal ECG monitoring. The proposed amplifier allows for individual tuning of the noise in each measurement channel, minimizing the total power consumption while satisfying all application requirements. The low-voltage current reuse topology exploits power optimization in both the current and the voltage domain, exploiting multiple supply voltages (0.3, 0.6 and 1.2 V). The power management circuitry providing the different supplies is optimized for high efficiency (peak charge-pump efficiency = 90%).The low-voltage amplifier together with its power management circuitry is implemented in a standard 0.18 μm CMOS process and characterized experimentally. The amplifier core achieves both good noise efficiency factor (NEF=1.74) and power efficiency factor (PEF=1.05). Experiments show that the amplifier core can provide a noise level of 0.34 μVrms in a 0.7 to 182 Hz band, consuming 1.17 μW power. The amplifier together with its power management circuitry consumes 1.56 μW, achieving a PEF of 1.41. The amplifier is also validated with adult ECG and pre-recorded fetal ECG measurements.

Toward a Multiscale Model of the Uterine Electrical Activity

A comprehensive multiscale model of the uterine muscle electrical activity would permit understanding the important link between the genesis and evolution of the action potential at the cell level and the process leading to labor. Understanding this link can open the way to more effective tools for the prediction of labor and prevention of preterm delivery. A first step toward the realization of such a model is presented here. By using as starting point a previously published model of the generation of the uterine muscle action potential at the cell level, a significant reduction of the model complexity is here achieved in order to simulate 2-D propagation of the cellular activity at the uterine tissue level, for tissue strips of arbitrary dimension. From the obtained dynamic behavior of the electrical activity simulated at the tissue level, the use of a previously validated volume conductor model at the organ level permits us to simulate the electrohysterogram as recorded on the abdominal surface by an electrode array. Qualitative evaluation of the model at the cell level and at the organ level confirms the potential of the proposed multiscale approach for further refinement and extension aiming at clinical application.

Inter-electrode delay estimators for electrohysterographic propagation analysis

Premature birth is a major cause of mortality and permanent dysfunctions. Several parameters derived from single channel electrohysterographic (EHG) signals have been considered to determine contractions leading to preterm delivery. The results are promising, but improvements are needed. As effective uterine contractions result from a proper action potential propagation, in this paper we focus on the propagation properties of EHG signals, which can be predictive of preterm delivery. Two standard delay estimators, namely maximization of the cross-correlation function and spectral matching, are adapted and implemented for the assessment of inter-electrode delays of propagating EHG signals. The accuracy of the considered standard estimators might be hampered by a poor inter-channel correlation. An improved dedicated approach is therefore proposed. By simultaneous adaptive estimation of the volume conductor transfer function and the delay, a dedicated method is conceived for improving the inter-channel signal similarity during delay calculation. Furthermore, it provides delay estimates without resolution limits and it is suitable for low sampling rates, which are appropriate for EHG recording. The three estimators were evaluated on EHG signals recorded on seven women. The dedicated approach provided more accurate estimates due to a 22% improvement of the initial average inter-channel correlation.

Modeling and Identification of the Electrohysterographic Volume Conductor by High-Density Electrodes

The surface electrohysterographic (EHG) signal represents the bioelectrical activity that triggers the mechanical contraction of the uterine muscle. Previous work demonstrated the relevance of the EHG signal analysis for fetal and maternal monitoring as well as for prognosis of preterm labor. However, for the introduction in the clinical practice of diagnostic and prognostic EHG techniques, further insights are needed on the properties of the uterine electrical activation and its propagation through biological tissues. An important contribution for studying these phenomena in humans can be provided by mathematical modeling. A five-parameter analytical model of the EHG volume conductor and the cellular action potential (AP) is proposed here and tested on EHG signals recorded by a grid of 64 high-density electrodes. The model parameters are identified by a least-squares optimization method that uses a subset of electrodes. The parameters representing fat and abdominal muscle thickness are also measured by echography. The mean correlation coefficient and standard deviation of the difference between the echographic and EHG estimates were 0.94 and 1.9 mm, respectively. No bias was present. These results suggest that the model provides an accurate description of the EHG AP and the volume conductor, with promising perspectives for future applications.

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.