# NICU Automatic Oxygen Control with Parameter and Disturbance Estimation

> **NIH NIH R21** · UNIVERSITY OF MISSOURI-COLUMBIA · 2021 · $187,589

## Abstract

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.

## Key facts

- **NIH application ID:** 10143268
- **Project number:** 5R21HD097594-02
- **Recipient organization:** UNIVERSITY OF MISSOURI-COLUMBIA
- **Principal Investigator:** Ramak R Amjad
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $187,589
- **Award type:** 5
- **Project period:** 2020-06-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10143268

## Citation

> US National Institutes of Health, RePORTER application 10143268, NICU Automatic Oxygen Control with Parameter and Disturbance Estimation (5R21HD097594-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10143268. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*