Serious illness in childhood is a rare occurrence, but accounts for 20% of childhood deaths. Early recognition and treatment of serious illness is vital if the child is to recover without long-term disability. It is known that vital signs such as heart rate, respiratory rate, temperature, and oxygen saturation can be used to identify children who are at high risk of serious illness. This thesis presents research into the development of a vital signs monitor, designed for use in the initial assessment of unwell children at their first point of contact with a medical practitioner. Child-friendly monitoring techniques are used to obtain vital signs, which can then be combined using data fusion techniques to assist clinicians in identifying children with serious illness. Existing normal ranges for heart rate and respiratory rate in childhood vary considerably, and do not appear to be based on clinical evidence. This thesis presents a systematic meta-analysis of heart rate and respiratory rate from birth to 18 years of age, providing evidence-based curves which can be used to assess the degree of abnormality in these important vital signs. Respiratory rate is particularly difficult to measure in children, but is known to be predictive of serious illness. Current methods of automated measurement can be distressing, or are time-consuming to apply. This thesis therefore presents a novel method for estimating the respiratory rate from an optical finger sensor, the pulse oximeter, which is routinely used in clinical practice. Information from multiple vital signs can be used to identify children at risk of serious illness. A number of data fusion techniques were tested on data collected from children attending primary and emergency care, and shown to outperform equivalent existing scoring systems when used to identify those with more serious illness.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:540239 |
| Date | January 2010 |
| Creators | Fleming, Susannah |
| Contributors | Tarassenko, Lionel |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:840d94b0-041f-4b15-8b37-c2e37c999f3e |
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