Model of Neonatal Infant Blood Oxygen Saturation

In this work, three different black box models were designed to model the blood oxygen saturation (SpO₂) of a neonatal infant. The inputs into each of the models where fraction of inspired oxygen, heart rate, and respiratory rate. The three modeling types used were fuzzy logic, neural network, and a transfer function model. Each model was trained on a window of data. The models were tuned using a design of experiments and the optimum window size was found for each model. The models were tested to see how long the model adequately represents the future SpO₂. The best model was found to be the transfer function model which adequately modeled the future SpO₂ for an average of 51.8 seconds.