Anirudh Thommandram

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Neonatal spells are cardiorespiratory events that occur in newborn infants with variable combinations of cessation of breathing, decrease in blood oxygen saturation and decrease in heart rate. A system using real-time temporal analysis of physiological data streams to accurately detect pauses in breathing and changes in heart rate and oxygen saturation for(More)
Apnoea is a sleep related breathing disorder that is common in adults and can be described as a temporary closure in the upper airway during sleep. A system using time series analysis of one minute epochs of respiratory impedance signals to detect apnoea is described. An algorithm has been developed using MATLAB for extracting clinically recognizable(More)
High speed physiological data produced by medical devices at intensive care units (ICUs) has all the characteristics of Big Data. The proper use and management of such data can promote the health and reduces mortality and disability rates of critical condition patients. The effective use of Big Data within ICUs has great potential to create new cloud-based(More)
We present a method for transmission and processing of real-time trans-continental medical data streams. We apply fundamentals of existing network technologies to create a secure tunnel from a remote hospital through an open-network to the Artemis Cloud. We capture and store incoming 1Hz data stream in our real-time event stream processor to allow for(More)
Neonatal spells are cardiorespiratory events that occur frequently in premature infants. Currently manual, nonspecific and ad-hoc identification of neonatal spells are documented by bedside clinical staff. A library of real-time streaming algorithms was developed to create real-time temporal analysis of high frequency data streams. In this paper we describe(More)
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