Evaluation of Pelvic Floor Muscles in Pregnancy and Postpartum With Non-Invasive Magnetomyography.

Objective: To record and characterize features of levator ani muscles (LAM) activity in pregnancy and postpartum using non-invasive and novel Magnetomyography (MMG) technique with amplitude and spectral parameters. Methods: Nulliparous women with uncomplicated pregnancies participated in the MMG data collection during rest and voluntary LAM contractions (Kegels) with modulated intensity in third trimester and approximately 2 months postpartum (PP). Simultaneous surface electromyography was recorded to document the recruitment of accessory muscles. Moderate strength Kegel (MK) MMG trials were analyzed. Amplitude and spectral parameters including root-mean square (RMS) amplitude, power spectrum density (PSD) and normalized PSD (rPSD) in three frequency bands (low, middle, high) were computed on MK epochs. Statistical comparisons between pregnancy and postpartum were calculated. Results: MMG recordings were measured from 10 pregnant women. Results showed decreased RMS and power between third trimester and postpartum, trending towards significance. rPSD values in the low frequency band decreased significantly (p = 0.028) from third trimester to postpartum, while significant increase was observed in the middle frequency band (p = 0.018). Conclusions: This study shows that MMG as non-invasive tool has the ability to detect and characterize changes of LAM activity with amplitude and spectral parameters during pregnancy and postpartum.

Connectivity Measures of Uterine Activity using Magnetomyography.

This work explores the use of graph-theoretical metrics of network topography to investigate interactions in the uterine activity using a multi-channel SQUID array. Magnetomyography (MMG) is a noninvasive technique that records magnetic fields associated with the uterine activity. Graph analysis was applied to 30s no-overlap epochs of MMG data for evaluating the evolution of local and global connectivity, and centrality indicators within the network. Binary graphs were obtained by applying a range of thresholds from 10% to 35% of the strongest edges preserved. Network analysis was applied to 24 simulated MMG data when independent noise realizations were added. Simulated data was generated from a multiscale forward model that uses a realistic uterus representation. Additionally, we applied network analysis to repeated real MMG measurements obtained from a subject at different gestational ages (GA) to observe the evolution of the network until subject reaches active labor. Results show in the simulation setting that network metrics were higher during the burst activity reflecting the propagation activity of the signal across the uterus of the multiscale mathematical model. The local efficiency values were higher than the global efficiency for any threshold used. For real MMG recordings, global and local efficiency, and clustering coefficient values increased as the patient approached active labor at any binarized threshold whereas betweenness centrality quantity decreased with days to active labor.

Coupling Analysis of Fetal and Maternal Heart Rates via Transfer Entropy Using Magnetocardiography.

Recent studies have shown that occasional short term coupling between fetal and maternal cardiac systems occurs. Fetal magnetocardiography (fMCG) is a non-invasive technique that records the magnetic fields associated with the electrical activity of the fetal heart through sensors placed over the maternal abdomen. The fMCG allows accurate estimation of fetal heart rates (fHR) due to its high signal-to-noise ratio (SNR) and temporal resolution. In this study, we analyzed couplingbetween fHR and maternal heart rates (mHR) using Transfer Entropy (TE). TE determines coupling between two variables by quantifying the information transferred between them in both directions. In this work, we used 74 fMCG recordings to compute TE in both directions over 1-minute disjoint time windows (TW). We examined the effect of fetal movement (FM) as a factor of influence on the TE analysis. We identified 21 subjects with FM during the recording and separated them into two gestational age (GA) groups (GA1<32 and GA2≥32 weeks). Next, TE values were compared between TWs containing non- FM with TWs containing FM using Wilcoxon Signed-Rank test. In addition, we compared TE calculations for non-FM segments obtained from the 74 subjects using Rank-Sum test in the two GA groups. Our results showed that TE values from TWs containing FM are not significantly different than those computed for TWs of non-FM. In both directions, we found that TE values obtained from the 74 subjects did not show any significant difference between GA1 and GA2 which is consistent with previous studies. Our study suggests that FM does not affect the TE computations.

Fetal auditory evoked responses to onset of amplitude modulated sounds. A fetal magnetoencephalography (fMEG) study.

The human fetal auditory system is functional around the 25th week of gestational age when the thalamocortical connections are established. Fetal magnetoencephalography (fMEG) provides evidence for fetal auditory brain responses to pure tones and syllables. Fifty-five pregnant women between 31 and 40 weeks of gestation were included in the study. Fetal MEG was recorded during the presentation of an amplitude modulated tone (AM) with a carrier frequency of 500 Hz to the maternal abdomen modulated by low modulation rates (MRs) - 2/s and 4/s, middle MR - 8/s and high MRs - 27/s, 42/s, 78/s and 91/s. The aim was to determine whether the fetal brain responds differently to envelope slopes and intensity change at the onset of the AM sounds. A significant decrease of the response latencies of transient event-related responses (ERR) to high and middle MRs in comparison to the low MRs was observed. The highest fetal response rate was achieved by modulation rates of 2/s, 4/s and 27/s (70%, 57%, and 86%, respectively). Additionally, a maturation effect of the ERR (response latency vs. gestational age) was observed only for 4/s MR. The significant difference between the response latencies to low, middle, and high MRs suggests that still before birth the fetal brain processes the sound slopes at the onset in different integration time-windows, depending on the time for the intensity increase or stimulus power density at the onset, which is a prerequisite for language acquisition.

Selection of Reference Channels Based on Mutual Information for Frequency-Dependent Subtraction Method Applied to Fetal Biomagnetic Signals.

OBJECTIVE: We propose a method that uses minimal redundancy and maximal relevance (mRMR) based on mutual information as criteria to automatically select references for the frequency-dependent subtraction (SUBTR) method to attenuate maternal (mMCG) and fetal (fMCG) magnetocardiograms of fetal magnetoencephalography recordings. METHODS: mRMR is calculated between all channels and mMCG/fMCG target channels and the most promising sensors are used as references to perform SUBTR. We measured the performance of SUBTR at removing interferences in two steps for different number of references in 38 real datasets. The evaluation was based on the MCG amplitude reduction. We compared the performance of the mRMR approach with random selection of references. RESULTS: Significant differences in interference removal were found when a distinct number of references were chosen by mRMR compared to random selection. CONCLUSION: mRMR provides an effective tool to automatically select a set of featured references. SIGNIFICANCE: Although we show the utility of the mRMR method to biomagnetic signals, the approach can easily be adapted to sensor array data from other applications.

Cardiac time intervals derived by magnetocardiography in fetuses exposed to pregnancy hypertension syndromes.

OBJECTIVE: To test the hypothesis that fetuses exposed to maternal preeclampsia or chronic hypertension have deranged development of cardiac time intervals. STUDY DESIGN: Pregnancies were divided into three groups: Intrauterine Growth Restricted (IUGR), Hypertensive, and Normal. Each group's mean fetal cardiac time intervals (P, PR, QRS and RR) derived by magnetocardiography were calculated using an analysis of covariance model's regression-adjusted estimates for a gestational age of 35 weeks. RESULTS: We reviewed 141 recordings from 21 IUGR, 46 Hypertensive and 74 Normal patients. The IUGR, Hypertensive and Normal groups, respectively, had adjusted mean intervals in milliseconds of 66.4, 66.8 and 76.2 for P (P=0.001), 95.9, 101.6 and 109.6 for PR (P=0.002), 77.2, 78.7 and 78.7 for QRS (P=0.81) and 429.8, 429.2 and 428.5 for RR (P=0.97). CONCLUSION: P and PR intervals are abbreviated in normotrophic fetuses exposed to maternal hypertension, suggesting shortened atrioventricular conduction times.

A computer-aided approach to detect the fetal behavioral states using multi-sensor Magnetocardiographic recordings.

We propose a novel computational approach to automatically identify the fetal heart rate patterns (fHRPs), which are reflective of sleep/awake states. By combining these patterns with presence or absence of movements, a fetal behavioral state (fBS) was determined. The expert scores were used as the gold standard and objective thresholds for the detection procedure were obtained using Receiver Operating Characteristics (ROC) analysis. To assess the performance, intraclass correlation was computed between the proposed approach and the mutually agreed expert scores. The detected fHRPs were then associated to their corresponding fBS based on the fetal movement obtained from fetal magnetocardiogaphic (fMCG) signals. This approach may aid clinicians in objectively assessing the fBS and monitoring fetal wellbeing.

Genetic algorithms for dipole location of fetal magnetocardiography.

In this paper, we explore the use of Maximum Likelihood (ML) method with Genetic Algorithms (GA) as global optimization procedure for source reconstruction in fetal magnetocardiography (fMCG) data. A multiple equivalent current dipole (ECD) model was used for sources active in different time samples. Inverse solutions across time were obtained for a single-dipole approximation to estimate the trajectory of the dipole position. We compared the GA and SIMPLEX methods in a simulation environment under noise conditions. Methods are applied on a real fMCG data. Results show robust estimators of the cardiac sources when GA is used as optimization technique.

Formation and validation of questionnaire to assess Jatharagni.

BACKGROUND: Jatharagni (metabolic fire) is of the prime importance in the maintenance of health as well as causation of diseases. Food which is consumed by the person shares the major responsibility for being healthy or manifestation of diseases. The relation between food and health is mediated by Jatharagni (the metabolic agent in Ayurveda). There are four different states of Jatharagni viz, Mandagni (mild or weak state of metabolic fire), Visamagni (irregular state of metabolic fire), Tiksnagni (sharp or intense state of metabolic fire), and Samagni (Normal state of metabolic fire). Samagni (Normal state of metabolic fire) is said to be the normal State and maintains the health of an individual. All the other states are considered as abnormal. OBJECTIVES: To frame and validate a Questionnaire to assess the state of Jatharagni. MATERIALS AND METHODS: A qualitative research that involved interview method and cluster sampling method. A total of 500 volunteers of either gender in two groups viz., apparently healthy and unhealthy were assessed for their Jatharagni. Questionnaire was framed with 64 items. A total of 14 questions under Visamagni (irregular state of metabolic fire), 13 under Tikshnagni, 13 under Mandagni and 24 questions under Samagni were framed. The questionnaire was in optional format with 5 item likert's scale pattern and the validation was done by Cronbach's Alpha for internal consistency. RESULT: The internal consistency of the questionnaire using Cronbach's Alpha was 0.916. The internal consistency of Visamagni domain was 0.909; Teekshnagni domain was 0.873; Mandagni domain was 0.894; and Samagni domain was 0.876. CONCLUSION: The internal consistency of the questionnaire was 0.909 which is indicative of the excellent internal consistency of questionnaire. The lacuna of tool to assess state of Jatharagni in Ayurveda is filled by this questionnaire.

Functional brain development in growth-restricted and constitutionally small fetuses: a fetal magnetoencephalography case-control study.

OBJECTIVE: Fetal magnetoencephalography records fetal brain activity non-invasively. Delayed brain responses were reported for fetuses weighing below the tenth percentile. To investigate whether this delay indicates delayed brain maturation resulting from placental insufficiency, this study distinguished two groups of fetuses below the tenth percentile: growth-restricted fetuses with abnormal umbilical artery Doppler velocity (IUGR) and constitutionally small-for-gestational-age fetuses with normal umbilical artery Doppler findings (SGA) were compared with fetuses of adequate weight for gestational age (AGA), matched for age and behavioural state. DESIGN: A case-control study of matched pairs. SETTING: Fetal magnetoencephalography-Center at the University Hospital of Tuebingen. POPULATION: Fourteen IUGR fetuses and 23 SGA fetuses were matched for gestational age and fetal behavioural state with 37 healthy, normal-sized fetuses. METHODS: A 156-channel fetal magentoencephalography system was used to record fetal brain activity. Light flashes as visual stimulation were applied to the fetus. The Student's t-test for paired groups was performed. MAIN OUTCOME MEASURE: Latency of fetal visual evoked magnetic responses (VER). RESULTS: The IUGR fetuses showed delayed VERs compared with controls (IUGR, 233.1 ms; controls, 184.6 ms; P = 0.032). SGA fetuses had similar evoked response latencies compared with controls (SGA, 216.1 ms; controls, 219.9 ms; P = 0.828). Behavioural states were similarly distributed. CONCLUSION: Visual evoked responses are delayed in IUGR fetuses, but not in SGA. Fetal behavioural state as an influencing factor of brain response latency was accounted for in the comparison. This reinforces that delayed brain maturation is the result of placental insufficiency.

Soil carbon stocks in Sarawak, Malaysia.

The relationship between greenhouse gas emission and climate change has led to research to identify and manage the natural sources and sinks of the gases. CO2, CH4, and N2O have an anthropic source and of these CO2 is the least effective in trapping long wave radiation. Soil carbon sequestration can best be described as a process of removing carbon dioxide from the atmosphere and relocating into soils in a form that is not readily released back into the atmosphere. The purpose of this study is to estimate carbon stocks available under current conditions in Sarawak, Malaysia. SOC estimates are made for a standard depth of 100 cm unless the soil by definition is less than this depth, as in the case of lithic subgroups. Among the mineral soils, Inceptisols tend to generally have the highest carbon contents (about 25 kg m(-2) m(-1)), while Oxisols and Ultisols rate second (about 10-15 kg m(-2) m(-1)). The Oxisols store a good amount of carbon because of an appreciable time-frame to sequester carbon and possibly lower decomposition rates for the organic carbon that is found at 1m depths. Wet soils such as peatlands tend to store significant amounts of carbon. The highest values estimated for such soils are about 114 kg m(-2) m(-1). Such appreciable amounts can also be found in the Aquepts. In conclusion, it is pertinent to recognize that degradation of the carbon pool, just like desertification, is a real process and that this irreversible process must be addressed immediately. Therefore, appropriate soil management practices should be instituted to sequester large masses of soil carbon on an annual basis. This knowledge can be used effectively to formulate strategies to prevent forest fires and clearing: two processes that can quickly release sequestered carbon to the atmosphere in an almost irreversible manner.

Removal of interference from fetal MEG by frequency dependent subtraction.

Fetal magnetoencephalography (fMEG) recordings are contaminated by maternal and fetal magnetocardiography (MCG) signals and by other biological and environmental interference. Currently, all methods for the attenuation of these signals are based on a time-domain approach. We have developed and tested a frequency dependent procedure for removal of MCG and other interference from the fMEG recordings. The method uses a set of reference channels and performs subtraction of interference in the frequency domain (SUBTR). The interference-free frequency domain signals are converted back to the time domain. We compare the performance of the frequency dependent approach with our present approach for MCG attenuation based on orthogonal projection (OP). SUBTR has an advantage over OP and similar template approaches because it removes not only the MCG but also other small amplitude biological interference, avoids the difficulties with inaccurate determination of the OP operator, provides more consistent and stable fMEG results, does not cause signal redistribution, and if references are selected judiciously, it does not reduce fMEG signal amplitude. SUBTR was found to perform well in simulations and on real fMEG recordings, and has a potential to improve the detection of fetal brain signals. The SUBTR removes interference without the need for a model of the individual interference sources. The method may be of interest for any sensor array noise reduction application where signal-free reference channels are available.

Bio-magnetic signatures of fetal breathing movement.

The purpose of fetal magnetoencephalography (fMEG) is to record and analyze fetal brain activity. Unavoidably, these recordings consist of a complex mixture of bio-magnetic signals from both mother and fetus. The acquired data include biological signals that are related to maternal and fetal heart function as well as fetal gross body and breathing movements. Since fetal breathing generates a significant source of bio-magnetic interference during these recordings, the goal of this study was to identify and quantify the signatures pertaining to fetal breathing movements (FBM). The fMEG signals were captured using superconducting quantum interference devices (SQUIDs) The existence of FBM was verified and recorded concurrently by an ultrasound-based video technique. This simultaneous recording is challenging since SQUIDs are extremely sensitive to magnetic signals and highly susceptible to interference from electronic equipment. For each recording, an ultrasound-FBM (UFBM) signal was extracted by tracing the displacement of the boundary defined by the fetal thorax frame by frame. The start of each FBM was identified by using the peak points of the UFBM signal. The bio-magnetic signals associated with FBM were obtained by averaging the bio-magnetic signals time locked to the FBMs. The results showed the existence of a distinctive sinusoidal signal pattern of FBM in fMEG data.

A novel approach to track fetal movement using multi-sensor magnetocardiographic recordings.

Changes in fetal magnetocardiographic (fMCG) signals are indicators for fetal body movement. We propose a novel approach to reliably extract fetal body movements based on the field strength of the fMCG signal independent of its frequency. After attenuating the maternal MCG, we use a Hilbert transform approach to identify the R-wave. At each R-wave, we compute the center-of-gravity (cog) of the coordinate positions of MCG sensors, each weighted by the magnitude of the R-wave amplitude recorded at the corresponding sensor. We then define actogram as the distance between the cog computed at each R-wave and the average of the cog from all the R-waves in a 3-min duration. By applying a linear de-trending approach to the actogram we identify the fetal body movement and compare this with the synchronous occurrence of the acceleration in the fetal heart rate. Finally, we apply this approach to the fMCG recorded simultaneously with ultrasound from a single subject and show its improved performance over the QRS-amplitude based approach in the visually verified movements. This technique could be applied to transform the detection of fetal body movement into an objective measure of fetal health and enhance the predictive value of prevalent clinical testing for fetal wellbeing.

Fetal MEG evoked response latency from beamformer with random field theory.

Analysis of fetal magnetoencephalographic brain recordings is restricted by low signal to noise ratio (SNR) and non-stationarity of the sources. Beamformer techniques have been applied to improve SNR of fetal evoked responses. However, until now the effect of non-stationarity was not taken into account in detail, because the detection of evoked responses is in most cases determined by averaging a large number of trials. We applied a windowing technique to improve the stationarity of the data by using short time segments recorded during a flash-evoked study. In addition, we implemented a random field theory approach for more stringent control of false-positives in the statistical parametric map of the search volume for the beamformer. The search volume was based on detailed individual fetal/maternal biometrics from ultrasound scans and fetal heart localization. Average power over a sliding window within the averaged evoked response against a randomized average background power was used as the test z-statistic. The significance threshold was set at 10% over all members of a contiguous cluster of voxels. There was at least one significant response for 62% of fetal and 95% of newborn recordings with gestational age (GA) between 28 and 45 weeks from 29 subjects. We found that the latency was either substantially unchanged or decreased with increasing GA for most subjects, with a nominal rate of about -11 ms/week. These findings support the anticipated neurophysiological development, provide validation for the beamformer model search as a methodology, and may lead to a clinical test for fetal cognitive development.

Verification of fetal brain responses by coregistration of fetal ultrasound and fetal magnetoencephalography data.

Fetal magnetoencephalography (fMEG) is used to study neurological functions of the developing fetus by measuring magnetic signals generated by electrical sources within the fetal brain. For this aim either auditory or visual stimuli are presented and evoked brain activity or spontaneous activity is measured at the sensor level. However a limiting factor of this approach is the low signal to noise ratio (SNR) of recorded signals. To overcome this limitation, advanced signal processing techniques such as spatial filters (e.g., beamformer) can be used to increase SNR. One crucial aspect of this technique is the forward model and, in general, a simple spherical head model is used. This head model is an integral part of a model search approach to analyze the data due to the lack of exact knowledge about the location of the fetal head. In the present report we overcome this limitation by a coregistration of volumetric ultrasound images with fMEG data. In a first step we validated the ultrasound to fMEG coregistration with a phantom and were able to show that the coregistration error is below 2 cm. In the second step we compared the results gained by the model search approach to the exact location of the fetal head determined on pregnant mothers by ultrasound. The results of this study clearly show that the results of the model search approach are in accordance with the location of the fetal head.

Understanding dynamics of the system using Hilbert phases: an application to study neonatal and fetal brain signals.

The Hilbert phase phi(t) of a signal x(t) exhibits slips when the magnitude of their successive phase difference |phi(t(i+1))-phi(t(i))| exceeds pi. By applying this approach to periodic, uncorrelated, and long-range correlated data, we show that the standard deviation of the time difference between the successive phase slips Deltatau normalized by the percentage of slips in the data is characteristic of the correlation in the data. We consider a 50x50 square lattice and model each lattice point by a second-order autoregressive (AR2) process. Further, we model a subregion of the lattice using a different set of AR2 parameters compared to the rest. By applying the proposed approach to the lattice model, we show that the two distinct parameter regions introduced in the lattice are clearly distinguishable. Finally, we demonstrate the application of this approach to spatiotemporal neonatal and fetal magnetoencephalography signals recorded using 151 superconducting quantum interference device sensors to identify the sensors containing the neonatal and fetal brain signals and discuss the improved performance of this approach over the traditionally used spectral approach.

Magnetomyographic recording and identification of uterine contractions using Hilbert-wavelet transforms.

We propose a multi-stage approach using Wavelet and Hilbert transforms to identify uterine contraction bursts in magnetomyogram (MMG) signals measured using a 151 magnetic sensor array. In the first stage, we decompose the MMG signals by wavelet analysis into multilevel approximate and detail coefficients. In each level, the signals are reconstructed using the detail coefficients followed by the computation of the Hilbert transform. The Hilbert amplitude of the reconstructed signals from different frequency bands (0.1-1 Hz) is summed up over all the sensors to increase the signal-to-noise ratio. Using a novel clustering technique, affinity propagation, the contractile bursts are distinguished from the noise level. The method is applied on simulated MMG data, using a simple stochastic model to determine its robustness and to seven MMG datasets.

Design of a light stimulator for fetal and neonatal magnetoencephalography.

The design, safety analysis and performance of a fetal visual stimulation system suitable for fetal and neonatal magnetoencephalography studies are presented. The issue of fetal, neonatal and maternal safety is considered and the maximum permissible exposure is computed for the maternal skin and the adult eye. The risk for neonatal eye exposure is examined. It is demonstrated that the fetus, neonate and mother are not at risk.

An objective assessment of fetal and neonatal auditory evoked responses.

OBJECTIVE: We propose to use cross-correlation function to determine significant fetal and neonatal evoked responses (ERs). METHODS: We quantify ERs by cross-correlation between the stimulus time series and the recorded brain signals. The statistical significance of the correlation is calculated by surrogate analysis. For validation of our approach we investigated a model which mimics the generation of ERs. The model assumes a fixed latency of the ER and contains two parameters, epsilon and lambda. Whether or not the system responds to a given stimulus is controlled by epsilon. The amount to which the system is excited from the base line (background activity) is governed by lambda. We demonstrate the technique by applying it to auditory evoked responses from four fetuses (21 records) between 27 and 39 weeks of gestational age and four neonates (eight records). RESULTS: The method correctly identified the ER and the latency incorporated in the model. A combined analysis of fetuses and neonates data resulted in a significant negative correlation between age and latency. CONCLUSIONS: The analysis of ER, especially for fetal and newborn recordings, should be based on advanced data analysis including the assessment of the significance of responses. The negative correlation between age and latency indicates the neurological maturation. SIGNIFICANCE: The proposed method can be used to objectively assess the ER in fetuses and neonates.