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H Eswaran

Publications and source records attributed to H Eswaran.

12 recordsLinked to original sources
PubMed2007

Searching for the best model: ambiguity of inverse solutions and application to fetal magnetoencephalography.

Fetal brain signals produce weak magnetic fields at the maternal abdominal surface. In the presence of much stronger interference these weak fetal fields are often nearly indistinguishable from noise. Our initial objective was to validate these weak fetal brain fields by demonstrating that they agree with the electromagnetic model of the fetal brain. The fetal brain model is often not known and we have attempted to fit the data to not only the brain source position, orientation and magnitude, but also to the brain model position. Simulation tests of this extended model search on fetal MEG recordings using dipole fit and beamformers revealed a region of ambiguity. The region of ambiguity consists of a family of models which are not distinguishable in the presence of noise, and which exhibit large and comparable SNR when beamformers are used. Unlike the uncertainty of a dipole fit with known model plus noise, this extended ambiguity region yields nearly identical forward solutions, and is only weakly dependent on noise. The ambiguity region is located in a plane defined by the source position, orientation, and the true model centre, and will have a diameter approximately 0.67 of the modelled fetal head diameter. Existence of the ambiguity region allows us to only state that the fetal brain fields do not contradict the electromagnetic model; we can associate them with a family of models belonging to the ambiguity region, but not with any specific model. In addition to providing a level of confidence in the fetal brain signals, the ambiguity region knowledge in combination with beamformers allows detection of undistorted temporal waveforms with improved signal-to-noise ratio, even though the source position cannot be uniquely determined.

Biophysical Phenomena↗
PubMed2006

Optimal reduction of MCG in fetal MEG recordings.

Recording fetal magnetoencephalographic (fMEG) signals in-utero is a demanding task due to biological interference, especially maternal and fetal magnetocardiographic (MCG) signals. A method based on orthogonal projection of MCG signal space vectors (OP) was evaluated and compared with independent component analysis (ICA). The evaluation was based on MCG amplitude reduction and signal-to-noise ratio of fetal brain signals using exemplary datasets recorded during ongoing studies related to auditory evoked fields. The results indicate that the OP method is the preferable approach for attenuation of MCG and for preserving the fetal brain signals in fMEG recordings.

Algorithms↗
PubMed2004

Time-frequency and coherence analysis of fMEG signals.

Fetal magnetoencephalographic (fMEG) measurements are performed with interference from the fetal and maternal magnetocardiogram (MCG). Fetal movement, fetal breathing, fetal eye blinks or eye rollings and maternal muscle-contraction may generate detectable signals. These factors can be called "interventions," which can be manifested in space and/or time. They make the fMEG signals nonstationary. By examining temporal relationship of the multi-channel records, we are able to find the spatial signature of these "interventions." The aim of this study is to examine nonstationarity in single channel and nonhomogeniety in multiple channels of the fMEG data. Preliminary results are reported here, and may be used in further studies, leading toward intervention identification, and ultimately fetal state determination.

Fetal Monitoring↗
PubMed2004

Spatial-temporal analysis of non-stationary fMEG data.

Magnetoencephalography (MEG) is a technique used to non-invasively record neuromagnetic fields generated by the human brain. Our new SARA (SQUID Array for Reproductive Assessment) is a unique MEG device designed specifically for the study of the fetal neurophysiology. During the acquistion of fetal magnetoencephalography (fMEG), many other interfering bio-magnetic signals are collected as well. Examples include the movement of fetus or muscle contraction of the mother. As a result, the recorded signals may show unexpected patterns, other than the target signal of interest. These interventions makes it difficult for a physician to assess the exact fetal condition, including its response to various stimuli. We propose using intervention analysis and spatial-temporal autoregressive moving average (STARMA) modeling to address the problem. STARMA is a statistical method that examines the relationship between the current observations as a linear combination of past observations, as well as observations at neighboring sites. Through intervention analysis, the change in pattern due to interfering signals can be well accounted for. When these interferences are removed, the end product is a template time series, or a typical signal from the target of interest thus providing a more reliable means to monitor the actual signals generated by the fetal brain and other organs of interest.

Female↗
PubMed2004

Human fetal brain imaging by magnetoencephalography: verification of fetal brain signals by comparison with fetal brain models.

Fetal magnetoencephalogram (fMEG) is measured in the presence of a large interference from maternal and fetal magnetocardiograms (mMCG and fMCG). This cardiac interference can be successfully removed by orthogonal projection of the corresponding spatial vectors. However, orthogonal projection redistributes the fMEG signal among channels. Such redistribution can be readily accounted for in the forward solution, and the signal topography can also be corrected. To assure that the correction has been done properly, and also to verify that the measured signal originates from within the fetal head, we have modeled the observed fMEG by two extreme models where the fetal head is assumed to be either electrically transparent or isolated from the abdominal tissue. Based on the measured spontaneous, sharp wave, and flash-evoked fMEG signals, we have concluded that the model of the electrically isolated fetal head is more appropriate for fMEG analysis. We show with the help of this model that the redistribution due to projection was properly corrected, and also, that the measured fMEG is consistent with the known position of the fetal head. The modeling provides additional confidence that the measured signals indeed originate from within the fetal head.

Algorithms↗
PubMed2003

[New perspectives in intrauterine surveillance with the fetal magnetoencephalogram].

PURPOSE: Despite intensive research and surveillance up to now one has failed to reduce cerebral handicaps in newborn. Fetal heart rate tracing (CTG) and Doppler have reduced the number of subpartal severe asphyxia and fetal death. But, 90% of cerebral damage is a result of antepartal problems. Thus only 10% can be avoided by intensive surveillance during labor. Detection of antenatal cerebral injury is a rare case and its impact on later fetal life can only be estimated. Insight in fetal neuronal function is not possible. Factors and time pattern determining fetal cerebral injury are thus not known. This publication explains a new system with whom one might be able to get more insight in cerebral wellbeing during the fetal intrauterine life. METHODS AND RESULTS: A new diagnostic approach is set up by recording fetal magnet encephalographic signals (fMEG) thus offering the opportunity to detect fetal brain function. An array which was especially designed to fit to the pregnant body consists of 151 sensors which are able to record the fMEG. Clinical testing is performed in the moment at the UAMS in Little Rock, Arkansas in Cooperation with the Institutes for Medical Psychology and the Frauenklinik in Tiibingen. First results and arising questions are published. CONCLUSION: With this new system a deeper insight into the fetal neuronal development and fetal wellbeing during pregnancy might be achieved thus reforming the fetal surveillance in the 21st century.

Brain↗
PubMed2003

Analysis of uterine contractions: a dynamical approach.

The development of suitable techniques for quantifying mechanical and electrophysiological aspects of uterine contractions has been an active area of research. The uterus is a physiological system consisting of a large number of interacting muscle cells. The activity of these cells evolves with time, a trait characteristic of a dynamical system. While such complex physiological systems are non-linear by their very nature, whether this non-linearity is exhibited in the external recording is far from trivial. Traditional techniques such as spectral analysis have been used in the past, but these techniques implicitly assume that the process generating the contractions is linear and hence may be biased. In this tutorial review, a systematic approach using a hierarchy of surrogate algorithms is used to determine the nature of the process generating the contractions produced during labor. The results reveal that uterine contractions are probably generated by non-linear processes. The contraction segments were obtained through simultaneous recordings of the electrical and magnetic signals corresponding to the electrophysiological activity of the uterus and then analyzed. The electrical activity was recorded by placement of non-invasive electrodes onto the maternal abdomen and magnetic activity was recorded non-invasively using a superconducting quantum interference device (SQUID).

Algorithms↗
PubMed2003

First magnetomyographic recordings of uterine activity with spatial-temporal information using 151 channel sensor array (SARA).

The lack of an effective method for the diagnosis and management of labor points to the need for a new device. SARA-SQUID Array for Reproductive Assessment, is capable of recording spatial-temporal biomagnetic activity. The SARA system is first of its kind in the world dedicated to maternal-fetal research. We non-invasively recorded the magnetomyographic (MMG) signals corresponding to the uterine electrical activity from 7 pregnant mothers. The detailed physiological information obtained simultaneously from 151 sensors spread over the entire abdomen, will help in understanding the origin and propagation of the uterine activity. This information could give us better insight into the mechanism of uterine contraction and may help in better diagnosis and management of labor.

Female↗
PubMed2002

Application of wavelet transform to uterine electromyographic signals recorded using abdominal surface electrodes.

OBJECTIVE: The aim of this study was to explore the use of the wavelet transform technique to extract and display simultaneously the time, frequency and amplitude information corresponding to electromyographic (EMG) activity of the uterus during labor recorded using abdominal electrodes. METHODS: Uterine EMG signals were recorded from patients in labor using three pairs of electrodes placed across the maternal abdomen. In all the patients uterine activity was also recorded either from an intrauterine pressure catheter (IUPC) or a tocodynamometer. The EMG signals were analyzed using spectral analysis and wavelet analysis. RESULTS: Uterine EMG bursts corresponded with uterine activity measured with either the IUPC or the tocodynamometer. Using wavelet analysis a time-frequency-amplitude plot was obtained to separate out the frequency components relating to uterine EMG activity. CONCLUSION: This study showed that the wavelet transform could be a useful tool to study the uterine EMG activity. Continued studies on frequency content, amplitude and origin of uterine EMG activity could be helpful in understanding uterine contraction.

Algorithms↗
PubMed1999

Brain stem auditory evoked potentials in the human fetus during labor.

OBJECTIVE: The aim of this study was to record, during labor, the brain stem auditory evoked potentials of the fetus from standard fetal scalp electrodes. STUDY DESIGN: A personal computer-based instrument was developed to record, during labor, brain stem auditory evoked potentials from 10 fetuses ranging in gestational age from 36 to >/=40 weeks. Auditory stimulus was provided by clicks (16/s) delivered on the mother's abdomen with an intensity of 120 dB. The evoked potential signals were digitized and averaged. Interfering artifacts were excluded from the averages. RESULTS: In 80% of the subjects, all the principal waveforms of the brain stem auditory evoked potentials-waves I, III, and V-were clearly identifiable. The latency for wave I ranged from 1.2 to 2.2 ms, wave III from 3.4 to 5.6 ms, and wave V from 5.8 to 8.4 ms. The morphologic features of the waveform and the interwave latency values were similar to those of normal term infants recorded in the past studies. CONCLUSION: We have reestablished that it is possible to record auditory evoked potentials during labor from fetal scalp electrodes. Brain stem auditory evoked potentials may be a useful screening tool for at least the severely neurologically damaged fetus.

Electrodes↗
PubMedDate not supplied

Challenges of recording human fetal auditory-evoked response using magnetoencephalography.

OBJECTIVE: Our goals were to successfully perform fetal auditory-evoked responses using the magnetoencephalography technique, understand its problems and limitations, and propose instrument design modifications to improve the signal quality and success rate. METHODS: Fetal auditory-evoked responses were recorded from four fetuses with gestational ages ranging from 33-40+ weeks. The signals were recorded using a gantry-based superconducting quantum interference device. Auditory stimulus was 1 kHz tone burst. The evoked signals were digitized and averaged over an 800 ms window. RESULTS: After several trials of positioning and repositioning the subjects, we were able to record auditory-evoked responses in three out of the four fetuses. Since the superconducting quantum interference device array design was not shaped to fit over the mother's abdomen, we experienced difficulty in positioning the sensors over the fetal head. CONCLUSIONS: Based on this pilot study, we propose instrument design that may improve signal quality and success rate of the fetal magnetic auditory-evoked response.

Equipment Design↗