Modeling and Feedback Control of Inspired Oxygen for Premature Infants

Premature infants are commonly treated for respiratory problems due to their underdeveloped lungs. Due to Respiratory Distress Syndrome, the infant requires mechanical ventilation or increased inspired oxygen. If the blood oxygen saturation is kept a too high of a level, the infant is at risk for retinopathy of prematurity. A safe level for the infant’s blood oxygen saturation is between 85–92%. An automatic control system would aid nurses in care of premature infants. Since each infant is different, the control system must be robust enough to achieve adequate control of the percentage of oxygen in inspired air administered to the patient. Clinical data is acquired from patient bedside monitors. A parameter estimating extended Kalman filter assuming a first order model is applied to the data to calculate a range of system gains and time constants. An error model is then created using the resulting ranges of parameters. Performance specifications are defined and a μ-synthesis controller is developed to automatically control the oxygen percentage of inspired air. The control system is analyzed using H_∞ methods to determine whether robust stability and robust performance are achieved in the presence of system uncertainty described by the error model.