title: Development and preclinical testing of an adaptive algorithm for automated control of inspired oxygen in the preterm infant.
abstract: OBJECTIVE
  To assess the performance of a novel algorithm for automated oxygen control using a simulation of oxygenation founded on in vivo data from preterm infants.
  
  
  METHODS
  A proportional-integral-derivative (PID) control algorithm was enhanced by (i) compensation for the non-linear SpO2-PaO2relationship, (ii) adaptation to the severity of lung dysfunction and (iii) error attenuation within the target range. Algorithm function with and without enhancements was evaluated by iterative linking with a computerised simulation of oxygenation. Data for this simulation (FiO2and SpO2at 1 Hz) were sourced from extant recordings from preterm infants (n=16), and converted to a datastream of values for ventilation:perfusion ratio and shunt. Combination of this datastream second by second with the FiO2values from the algorithm under test produced a sequence of novel SpO2values, allowing time in the SpO2target range (91%-95%) and in various degrees of hypoxaemia and hyperoxaemia to be determined. A PID algorithm with 30 s lockout after each FiO2adjustment, and a proportional-derivative (PD) algorithm were also evaluated.
  
  
  RESULTS
  Separate addition of each enhancing feature to the PID algorithm showed a benefit, but not with uniformly positive effects. The fully enhanced algorithm was optimal for the combination of targeting the desired SpO2range and avoiding time in, and episodes of, hypoxaemia and hyperoxaemia. This algorithm performed better than one with a 30 s lockout, and considerably better than PD control.
  
  
  CONCLUSIONS
  An enhanced PID algorithm was very effective for automated oxygen control in a simulation of oxygenation, and deserves clinical evaluation.
authors.affiliation: Neonatal Respiratory Group, Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia.|Department of Paediatrics, Royal Hobart Hospital, Hobart, Tasmania, Australia.
authors.forename: Peter A
authors.initials: PA
authors.lastname: Dargaville
authors.affiliation: School of Engineering and ICT, University of Tasmania, Hobart, Tasmania, Australia.
authors.forename: Omid
authors.initials: O
authors.lastname: Sadeghi Fathabadi
authors.affiliation: Department of Paediatrics, Royal Hobart Hospital, Hobart, Tasmania, Australia.|School of Medicine, University of Tasmania, Hobart, Tasmania, Australia.
authors.forename: Gemma K
authors.initials: GK
authors.lastname: Plottier
authors.affiliation: Department of Paediatrics, Royal Hobart Hospital, Hobart, Tasmania, Australia.
authors.forename: Kathleen
authors.initials: K
authors.lastname: Lim
authors.affiliation: Neonatal Unit, Royal Children's Hospital, Melbourne, Victoria, Australia.
authors.forename: Kevin I
authors.initials: KI
authors.lastname: Wheeler
authors.affiliation: School of Engineering and ICT, University of Tasmania, Hobart, Tasmania, Australia.
authors.forename: Rohan
authors.initials: R
authors.lastname: Jayakar
authors.affiliation: School of Engineering and ICT, University of Tasmania, Hobart, Tasmania, Australia.
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Gale
mesh_terms: D000465:Algorithms; D001331:Automation / Q000379:methods*; D005260:Female; D006801:Humans; D007231:Infant, Newborn; D007234:Infant, Premature; D007235:Infant, Premature, Diseases / Q000628:therapy*; D008297:Male; D010092:Oximetry; D010100:Oxygen / Q000008:administration & dosage*; D010102:Oxygen Inhalation Therapy / Q000379:methods*; D012121:Respiration, Artificial / Q000379:methods*
chemical_list: D010100:Oxygen
keywords: Intensive Care; Neonatology; Respiratory