Non-invasive measurement of respiratory rate in children using the photoplethysmogram.
Respiratory rate is recognised as a valuable predictor of the severity of illness in children, but it is not currently feasible to measure this automatically in a triage environment. Autoregressive modelling on data from the pulse oximeter photoplethysmogram has the potential to introduce automated breathing measurement into the realm of paediatric triage. Using autoregressive modelling, it is shown that respiratory rate can be extracted from the paediatric photoplethysmogram with a mean error of 3.4 breaths per minute.
Fleming
Susannah
S
Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, OX3 7DQ, UK.
Tarassenko
Lionel
L
Thompson
Matthew
M
Mant
David
D
D001698:Biomedical Engineering; D002648:Child; D006801:Humans; D008991:Monitoring, Physiologic / Q000295:instrumentation / Q000379:methods / Q000706:statistics & numerical data; D017156:Photoplethysmography / Q000295:instrumentation / Q000379:methods* / Q000706:statistics & numerical data; D012044:Regression Analysis; D012119:Respiration