Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

The field of electrocardiography has been in existence for over a century, yet despite significant advances in adult clinical electrocardiography, signal processing techniques and fast digital processors, the analysis of fetal ECGs is still in its infancy. This is, partly due to a lack of availability of gold standard databases, partly due to the relatively low signal-to-noise ratio of the fetal ECG compared to the maternal ECG (caused by the various media between the fetal heart and the measuring electrodes, and the fact that the fetal heart is simply smaller), and in part, due to the less complete clinical knowledge concerning fetal cardiac function and development. In this paper we review a range of promising recording and signal processing techniques for fetal ECG analysis that have been developed over the last forty years, and discuss both their shortcomings and advantages. Before doing so, however, we review fetal cardiac development, and the etiology of the fetal ECG. A selection of relevant models for the fetal/maternal ECG mixture is also discussed. In light of current understanding of the fetal ECG, we then attempt to justify recommendations for promising future directions in signal processing, and database creation.

/pdf/a-review-of-fetal-ecg-signal-processing-issues-and-promising-4rrwzf0zes.pdf

A Review of Fetal ECG Signal Processing; Issues and Promising Directions.

Antibiotics for asymptomatic bacteriuria in pregnancy.

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Medical Instrumentation Application And Design

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Bioelectrical Signal Processing In Cardiac And Neurological Applications

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.

https://iopscience.iop.org/article/10.1088/0967-3334/28/4/004/pdf

A robust fetal ECG detection method for abdominal recordings

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.

https://iopscience.iop.org/article/10.1088/0967-3334/29/7/011/pdf

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

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.

/pdf/noninvasive-estimation-of-the-electrohysterographic-action-26gju45on7.pdf

Noninvasive Estimation of the Electrohysterographic Action-Potential Conduction Velocity

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 (03, 06 and 12 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 $018~\mu{\rm m}$ CMOS process and characterized experimentally The amplifier core achieves both good noise efficiency factor $({\rm NEF}=174)$ and power efficiency factor $({\rm PEF}=105)$  Experiments show that the amplifier core can provide a noise level of $034~\mu {\rm Vrms}$ in a 07 to 182 Hz band, consuming $117~\mu {\rm W}$ power The amplifier together with its power management circuitry consumes $156 ~\mu {\rm W}$ , achieving a PEF of 141 The amplifier is also validated with adult ECG and pre-recorded fetal ECG measurements

/pdf/a-low-voltage-chopper-stabilized-amplifier-for-fetal-ecg-1q83jmpffm.pdf

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

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.

https://iopscience.iop.org/article/10.1088/0967-3334/33/7/1135/pdf

Chiara Rabotti

Papers

A robust fetal ECG detection method for abdominal recordings

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

Noninvasive Estimation of the Electrohysterographic Action-Potential Conduction Velocity

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

Low-complexity R-peak detection for ambulatory fetal monitoring