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)
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)
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)
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)
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