Fetal source extraction from magnetocardiographic recordings by dependent component analysis

Comparative Effectiveness of ICA and PCA in Extraction of Fetal ECG From Abdominal Signals: Toward Non-invasive Fetal Monitoring

Non-adaptive signal processing methods have been successfully applied to extract fetal electrocardiograms (fECGs) from maternal abdominal electrocardiograms (aECGs); and initial tests to evaluate the efficacy of these methods have been carried out by using synthetic data. Nevertheless, performance evaluation of such methods using real data is a much more challenging task and has neither been fully undertaken nor reported in the literature. Therefore, in this investigation, we aimed to compare the effectiveness of two popular non-adaptive methods (the ICA and PCA) to explore the non-invasive (NI) extraction (separation) of fECGs, also known as NI-fECGs from aECGs. The performance of these well-known methods was enhanced by an adaptive algorithm, compensating amplitude difference and time shift between the estimated components. We used real signals compiled in 12 recordings (real01-real12). Five of the recordings were from the publicly available database (PhysioNet-Abdominal and Direct Fetal Electrocardiogram Database), which included data recorded by multiple abdominal electrodes. Seven more recordings were acquired by measurements performed at the Institute of Medical Technology and Equipment, Zabrze, Poland. Therefore, in total we used 60 min of data (i.e., around 88,000 R waves) for our experiments. This dataset covers different gestational ages, fetal positions, fetal positions, maternal body mass indices (BMI), etc. Such a unique heterogeneous dataset of sufficient length combining continuous Fetal Scalp Electrode (FSE) acquired and abdominal ECG recordings allows for robust testing of the applied ICA and PCA methods. The performance of these signal separation methods was then comprehensively evaluated by comparing the fetal Heart Rate (fHR) values determined from the extracted fECGs with those calculated from the fECG signals recorded directly by means of a reference FSE. Additionally, we tested the possibility of non-invasive ST analysis (NI-STAN) by determining the T/QRS ratio. Our results demonstrated that even though these advanced signal processing methods are suitable for the non-invasive estimation and monitoring of the fHR information from maternal aECG signals, their utility for further morphological analysis of the extracted fECG signals remains questionable and warrants further work.

Separation of Physiological Signals Using Minimum Norm Projection Operators

OBJECTIVE

This paper presents the development of a fast and robust method which can be applied to multichannel physiologic signals for the purpose of either removing a selected interfering signal or separating signals that arise from temporally correlated and spatially distributed signals such as maternal or fetal cardiac waveform recordings.

METHODS

Projection operators based upon both the weighted and un-weighted minimum norm equations are presented. The weighted formulation uses models based on signal covariance and the un-weighted formulation requires that a statistical model be built using time-locked averaging.

RESULTS

We present examples that demonstrate the utility of our projection operators when applied to maternal and fetal magneto-cardiograms. In addition, we demonstrate the ability to separate fetal breathing signals from both maternal and fetal cardiac signals.

CONCLUSION

The method is effective, robust, fast, and does not require significant input from a user.

SIGNIFICANCE

Although we demonstrate the utility of our projection operators applied to biomagnetic signals, the method can easily be adapted to other applications were the goal is to either separate or suppress selected signal components.

Cardiac vectors in the healthy human fetus: developmental changes assessed by magnetocardiography and realistic approximations of the volume conductor

This study sought to characterize the developmental changes of three measures used to describe the morphology of the fetal cardiac vector: QRS peak-amplitude, QRS duration and QRS time-amplitude integral. To achieve this objective, we rely on a recently developed methodology for fetal cardiac vector estimation, using multichannel fetal magnetocardiographic (fMCG) recordings and realistic approximations of the volume conductors obtained from free-hand ultrasound imaging. fMCG recordings and 3D ultrasound images were obtained from 23 healthy, uncomplicated pregnancies for a total of 77 recordings performed at gestational ages between 22 and 37 weeks. We report the developmental changes of the cardiac vector parameters with respect to gestational age and estimated fetal weight, as well as their dependence on the estimated ventricular mass derived from cardiac dimensions measured with M-mode ultrasound. The normative values can be used along with the cardiac time intervals reported by previous fMCG studies to assist future clinical studies investigating conditions that affect fetal cardiac function.

Detection of auditory cortex activity by fMRI using a dependent component analysis

Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM), which is the most widely used method to analyze fMRI datasets.

Non-extensive entropy and the extraction of BOLD spatial information in event-related functional MRI

Functional magnetic resonance imaging (fMRI) data analysis has been carried out recently in the framework of information theory, by means of the Shannon entropy. As a natural extension, a method based on the generalized Tsallis entropy was developed to the analysis event-related (ER-fMRI), where a brief stimulus is presented, followed by a long period of rest. The new technique aims for spatial localization neuronal activity due to a specific task. This method does not require a priori hypothesis of the hemodynamic response function (HRF) shape and the linear relation between BOLD responses with the presented task. Numerical simulations were performed so as to determine the optimal values of the Tsallis q parameter and the number of levels, L. In order to avoid undesirable divergences of the Tsallis entropy, only positive q values were studied. Results from simulated data (with L = 3) indicated that, for q = 0.8, the active brain areas are detected with the highest performance. Moreover, the method was tested for an in vivo experiment and demonstrated the ability to discriminate active brain regions that selectively responded to a bilateral motor task.

Dependent component analysis for the magnetogastrographic detection of human electrical response activity

The detection of the basic electric rhythm (BER), composed of a 3 cycles min(-1) oscillation, can be performed using SQUID magnetometers. However, the electric response activity (ERA), which is generated when the stomach is performing a mechanical activity, was detected mainly by invasive electrical measurements and only recently was one report published describing its detection by magnetic measurements. This study was performed with the aim of detecting the ERA noninvasively after a meal. MGG recordings were made with a 74-channel first-order gradiometer (Magnes II, biomagnetic technologies) housed in a shielded room. Seven nonsymptomatic volunteers were measured in the study. Initially a 10 min recording was performed with the subject in the fasted state. A 250 kcal meal was given to the subject without moving out of the magnetometers and two epochs of 10 min each were acquired. The signals were processed to remove cardiac interference by an algorithm based on a variation of independent component analysis (ICA), then autoregressive and wavelet analysis was performed. Preliminary results have shown that there is an increase in the signal power at higher frequencies around (0.6 Hz-1.3 Hz) usually associated with the basic electric rhythm. The center of the frequency band and its width varied from subject to subject, demonstrating the importance of pre-prandial acquisition as a control. Another interesting finding was an increase in power after about 5 min of meal ingestion. This period roughly agrees with the lag phase of gastric emptying, measured by scintigraphy and other techniques. We confirm that MGG can detect the electric response activity in normal volunteers. Further improvements in signal processing and standardization of signal acquisition are necessary to ascertain its possible use in clinical situations.

Magnetographic assessment of fetal hiccups and their effect on fetal heart rhythm

Fetal hiccups emerge as early as nine weeks post-conception, being the predominant diaphragmatic movement before 26 weeks of gestation. They are considered as a programmed isometric inspiratory muscle exercise of the fetus in preparation for the post-natal respiratory function, or a manifestation of a reflex circuitry underlying the development of suckling and gasping patterns. The present paper provides the first evidence of non-invasive biomagnetic measurements of the diaphragm spasmodic contractions associated with fetal hiccups. The magnetic field patterns generated by fetal hiccups exhibit well-defined morphological features, consisting of an initial high frequency transient waveform followed by a more prolonged low frequency component. This pattern is consistent across recordings obtained from two fetal subjects, and it is confirmed by signals recorded in a neonatal subject. These results demonstrate that fetal biomagnetometry can provide insights into the electrophysiological mechanisms of diaphragm motor function in the fetus. Additionally, we study the correlation between hiccup events and fetal cardiac rhythm and provide evidence that hiccups may modulate the fetal heart rate during the last trimester of pregnancy.