Srinivasan Vairavan

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The discontinuous patterns in neonatal magnetoencephalographic (MEG) data are quantified with a novel Hilbert phase (HP) based approach. The expert neurologists' scores were used as the gold standard. The performance of this approach was analyzed using a receiver operating characteristic (ROC) curve, and it was compared with two other approaches, namely(More)
We propose a novel method to characterize the spontaneous brain signals using Hilbert phases. The Hilbert phase of a signal exhibits phase slips when the magnitude of the successive phase difference exceeds pi. To this end we use standard deviation (sigmaDeltatau) of the time (Deltatau) between successive phase slips to characterize the signals. We(More)
Acute lung injury (ALI) is a devastating complication of acute illness and one of the leading causes of multiple organ failure and mortality in the intensive care unit (ICU). The detection of this syndrome is limited due to the complexity of the disease, insufficient understanding of its development and progression, and the large amount of risk factors and(More)
The fetal brain remains inaccessible to neurophysiological studies. Magnetoencephalography (MEG) is being assessed to fill this gap. We performed 40 fetal MEG (fMEG) recordings with gestational ages (GA) ranging from 30 to 37 weeks. The data from each recording were divided into 15 second epochs which in turn were classified as continuous (CO),(More)
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(More)
OBJECTIVE To identify quantitative MEG indices of spontaneous brain activity for fetal neurological maturation in normal pregnancies and examine the effect of fetal state on these indices. METHODS Spontaneous MEG brain activity was examined in 22 low-risk fetal recordings with gestational age (GA) ranging from 30 to 37 weeks. As major quantitative(More)
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(More)
The fetal magnetoencephalogram (fMEG) is measured in the presence of large interference from maternal and fetal magnetocardiograms (mMCG and fMCG). These cardiac interferences can be attenuated by orthogonal projection (OP) technique of the corresponding spatial vectors. However, the OP technique redistributes the fMEG signal among the channels and also(More)
We propose a novel approach based on Hilbert phase to identify the burst in the uterine myometrial activity. We apply this approach to 24 serial magnetomyographic signals recorded from four pregnant women using a 151 SQUID array system. The bursts identified with this approach are evaluated for duration and are correlated with the gestational age. In all(More)
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