NICU Automatic Oxygen Control with Parameter and Disturbance Estimation

项目总结/摘要 本研究的目的是展示一种新的自适应氧气控制系统， 改善正在接受呼吸机治疗的早产儿的氧饱和度控制 由于肺部发育不全而无法支撑。在这项工作中，将在两个地点进行临床研究 为了演示能够连续调节氧气的氧气控制装置， 的自动本研究是一项等同性交叉研究，旨在证明器械在以下条件下的性能： 在限制FiO 2波动和将SpO 2维持在 治疗医师规定的特定参数。如果有足够的证据， 将被调查。此外，该研究将产生的结果，将表征性能 手动和自动控制的替代方案，可以比较。 这项工作是正在进行的努力的一部分，以开发一种新的技术，用于控制氧气在 早产儿呼吸支持系统。关键的结果是临床数据， 早产儿氧气自动控制如何影响氧气控制的准确性 与手动控制相比的饱和度。这项工作的影响是， 将开发和测试一个控制系统，该系统将通过以下措施提高病人护理的一致性 自动调整控制算法，以适应每个病人，并将导致更好的理解 新生儿对氧气控制的反应动力学。 新的专利氧气控制技术使用参数估计扩展卡尔曼 使用测量的时间历史来估计动态模型的滤波器（PE-EKF 因此，氧气控制系统可以适应患者的各种参数， 患者的特征和条件。扰动估计器也估计扰动 由于未建模的输入导致氧饱和度的不利变化。扰动 估计允许控制系统快速量化干扰水平，并通过 操纵吸入的氧气以抵消引起去饱和事件的干扰。的 在系统建模、干扰估计器和PE-EKF方面的新发展允许实时 氧气控制系统在早期发育期间适应患者的变化 以及生理变化的开始。在这项工作中，研究人员将调查一种 先进的氧气控制系统，其设计基于 临床测试和系统动力学分析，以进一步提高性能。

PROJECT SUMMARY/ABSTRACT The goal of this research is to demonstrate a novel adaptive oxygen control system which will improve the control of oxygen saturation in premature infants who are receiving respiratory support due to underdeveloped lungs. In this work, a clinical study at two sites will be conducted to demonstrate an oxygen control device which is able to continuously adjust oxygen automatically. The study is an equivalence crossover to demonstrate that the device performs at least as well as a trained NICU nurse in limiting fluctuations in FiO2 and maintaining SpO2 within specific parameters prescribed by the treating physician. If there is sufficient evidence, superiority will be investigated. In addition, the study will yield results that will characterize the performance of manual and automatic control alternatives that can be compared. This work is part of an ongoing effort to develop a new technology for controlling oxygen in respiratory support systems for premature infants. The key outcome is clinical data that will show how automatic control of oxygen in premature infants affects the accuracy of control of the oxygen saturation level compared to manual control. The impact of this work is that a novel automatic control system will be developed and tested which will improve the consistency of patient care by automatically adapting the control algorithm to each patient and will lead to a better understanding of the dynamics of the response of neonates to oxygen control. The new patented oxygen control technology uses a parameter estimating extended Kalman filter (PE-EKF) that uses the time history of measurements to estimate the dynamic model parameters of the patients so that the oxygen control system can adapt to a wide range of patient characteristics and conditions. A disturbance estimator also estimates the disturbance level due to unmodeled inputs which cause adverse changes in oxygen saturation. Disturbance estimation allows the control system to quickly quantify the disturbance level and respond by manipulating inspired oxygen to cancel out disturbances that cause desaturation events. The new developments in modeling the system, disturbance estimator, and PE-EKF allow real-time adaptation of the oxygen control system to the changes in the patient during early development and the onset physiological changes. In this work, researchers will be investigating an advanced oxygen control system with a design based on the performance observed during clinical testing and analysis of the system dynamics to further improve the performance.