Title: Automated prediction of deterioration of infants in paediatric intensive care using SpO₂

Authors: B. Rajeswari Matam; Heather Duncan; David Lowe

Addresses: Paediatric Intensive Care Unit, Birmingham Children's Hospital, Birmingham, UK ' Paediatric Intensive Care Unit, Birmingham Children's Hospital, Birmingham, UK ' NCRG, Mathematics Group, Aston University, Birmingham, UK

Abstract: Acute life-threatening events are mostly predictable in adults and children. Despite real-time monitoring these events still occur at a rate of 4%. This paper describes an automated prediction system based on the feature space embedding and time series forecasting methods of the SpO₂ signal; a pulsatile signal synchronised with heart beat. We develop an age-independent index of abnormality that distinguishes patient-specific normal to abnormal physiology transitions. Two different methods were used to distinguish between normal and abnormal physiological trends based on SpO₂ behaviour. The abnormality index derived by each method is compared against the current gold standard of clinical prediction of critical deterioration.

Keywords: biomedical time series; critical event inference; feature space embedding; paediatric intensive care; infant deterioration; automated prediction; time series forecasting; pulsatile signals; heart beats; abnormalities; abnormal physiology transitions; infants.

DOI: 10.1504/IJBET.2013.058536

International Journal of Biomedical Engineering and Technology, 2013 Vol.13 No.4, pp.341 - 356

Received: 26 Dec 2012
Accepted: 28 Sep 2013
Published online: 27 Sep 2014 *

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