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Original article
Development and preclinical testing of an adaptive algorithm for automated control of inspired oxygen in the preterm infant
  1. Peter A Dargaville1,2,
  2. Omid Sadeghi Fathabadi3,
  3. Gemma K Plottier2,4,
  4. Kathleen Lim2,
  5. Kevin I Wheeler5,
  6. Rohan Jayakar3,
  7. Timothy J Gale3
  1. 1Neonatal Respiratory Group, Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
  2. 2Department of Paediatrics, Royal Hobart Hospital, Hobart, Tasmania, Australia
  3. 3School of Engineering and ICT, University of Tasmania, Hobart, Tasmania, Australia
  4. 4School of Medicine, University of Tasmania, Hobart, Tasmania, Australia
  5. 5Neonatal Unit, Royal Children's Hospital, Melbourne, Victoria, Australia
  1. Correspondence to Professor Peter A Dargaville, Department of Paediatrics, Royal Hobart Hospital, 48 Liverpool St, Hobart TAS 7000, Australia; peter.dargaville{at}dhhs.tas.gov.au

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–PaO2 relationship, (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 (FiO2 and SpO2 at 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 FiO2 values from the algorithm under test produced a sequence of novel SpO2 values, allowing time in the SpO2 target range (91%–95%) and in various degrees of hypoxaemia and hyperoxaemia to be determined. A PID algorithm with 30 s lockout after each FiO2 adjustment, 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 SpO2 range 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.

  • Neonatology
  • Respiratory
  • Intensive Care

https://doi.org/10.1136/archdischild-2016-310650

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    Footnotes

    • Contributors PAD: conceived the algorithm (with TJG) and its enhancements (with OSF, KIW and TJG), conceived and developed the simulation (with TJG and RJ), compiled and analysed the simulation data, wrote the first draft of the manuscript and approved the final version. OSF, GKP and KIW: identified enhancements to the function of the algorithm, reviewed and edited the manuscript and approved the final version. KL: collected the original data recordings used for simulation, reviewed and edited the manuscript and approved the final version. RJ: developed the simulation (with PAD), reviewed and edited the manuscript and approved the final version. TJG: conceived the algorithm (with PAD) and its enhancements (with PAD, OSF and KIW), conceived and developed the simulation (with PAD and RJ), reviewed and edited the manuscript and approved the final version.

    • Funding Supported by a starter grant (12-019) from the Royal Hobart Hospital Research Foundation.

    • Competing interests The University of Tasmania and Royal Hobart Hospital have jointly lodged a provisional patent application concerning automated control of inspired oxygen concentration in the newborn infant.

    • Ethics approval University of Tasmania Human Research Ethics Committee.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement Original data available for sharing on request.

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