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A computer model of the neonatal oxygen transport system containing a four compartment respiratory sub-system linked to a 13 compartment cardiovascular sub-system was developed in the first part of this paper. In this part, three 1 h supervisory programs were written to represent 3 neonate types: Baby 1 - stable but active; Baby 2 - unstable and not active; Baby 3 - unstable, not active and changing oxygen affinity. Next, simulations for three different types of controllers are described: manual, PID and fuzzy logic (FL). Finally, an in depth comparison of theses control alternatives was performed based on the results obtained by application to each of the three neonate types. [ABSTRACT FROM AUTHOR]

A computer model of the neonatal oxygen transport system is developed based on an adult model consisting of the respiratory and circulatory systems. A four compartment (mouth, trachea, bronchi and alveoli) respiratory system of adult is modelled using an RC circuit analogy and a sinusoidal driving function. The adult circulatory system is modelled as nine mixing chambers and four delay compartments. The oxygen dissociation curve is used to link the two systems. Allometric equations and empirical data are used to scale the adult model to a 1500 g neonate. Dynamic shunting and oxygen affinity adjustment are supported as a means of accommodating future development in the field of automatic neonatal oxygen therapy. Neonatal model values for arterial blood oxygen saturation (SaO2) and alveolar oxygen partial pressure (PAO2) are found to be comparable to physiological data. [ABSTRACT FROM AUTHOR]

Background: Within the context of automating neonatal oxygen therapy, this article describes the transformation of an idea verified by a computer model into a device actuated by a computer model. Computer modeling of an entire neonatal oxygen therapy system can facilitate the development of closed-loop control algorithms by providing a verification platform and speeding up algorithm development., Methods: In this article, we present a method of mathematically modeling the system's components: the oxygen transport within the patient, the oxygen blender, the controller, and the pulse oximeter. Furthermore, within the constraints of engineering a product, an idealized model of the neonatal oxygen transport component may be integrated effectively into the control algorithm of a device, referred to as the adaptive model. Manual and closed-loop oxygen therapy performance were defined in this article by 3 criteria in the following order of importance: percent duration of SpO2 spent in normoxemia (target SpO2 ± 2.5%), hypoxemia (less than normoxemia), and hyperoxemia (more than normoxemia); number of 60-second periods <85% SpO2 and >95% SpO2; and number of manual adjustments., Results: Results from a clinical evaluation that compared the performance of 3 closed-loop control algorithms (state machine, proportional-integral-differential, and adaptive model) with manual oxygen therapy on 7 low-birth-weight ventilated preterm babies, are presented. Compared with manual therapy, all closed-loop control algorithms significantly increased the patients' duration in normoxemia and reduced hyperoxemia (P < 0.05). The number of manual adjustments was also significantly reduced by all of the closed-loop control algorithms (P < 0.05)., Conclusions: Although the performance of the 3 control algorithms was equivalent, it is suggested that the adaptive model, with its ease of use, may have the best utility.