# CPS: AutoWean: Foundations of Autonomous Medical CPS for Mechanical Ventilation Weaning

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2021 · $382,956

## Abstract

While mechanical ventilators provide life-saving respiratory support, prolonged acute mechanical ventilation
(PAMV) can lead to severe complications (e.g. , pneumonia) and increased healthcare costs - predicted to
be over $32 billion in 2020 and accounting for over 10% of all hospital costs. Thus, mechanical ventilation
needs to be discontinued as early as possible, often by using a process known as "weaning". However, the
best approach to weaning remains an open question and is subject to controversy, where estimated
170,000 preventable deaths per year in US intensive care units are a result of inappropriate ventilator
weaning. Consequently, the Emergency Care Research Institute (ECRI) lists improper ventilator settings as
a Top 10 Health Technology Hazard in 2019.
 Autonomous mechanical ventilation weaning exemplifies a medical cyber-physical systems (MCPS) that
requires collections of interconnected medical devices (e.g., ventilators and patient monitors) that are
coordinated for treating a patient (i.e. , performing safe autonomous weaning). This proposal aims to
develop fundamental advances in safe and effective data-driven context-aware human-in-the-loop control
that will enable autonomous mechanical ventilation weaning . While closed-loop control and data-driven
techniques (e.g., system identification and machine learning) have been applied to MCPS, assuring the
safety and reliability of using data-driven components that adapt in-the-loop with a human operator remains
a challenge. We will demonstrate the impact of our closed-loop design and analysis techniques in
autonomous MCPS for mechanical ventilation weaning .
 The proposed project directly aligns with the mission of the National Institute of Biomedical Imaging and
Bioengineering (NIBIB) through the research and development of new technologies to advance medical
care through medical device interoperability and clinical decision support for enabling autonomous
mechanical ventilation weaning. Also relevant to the NIBIB mission, achieving the aims of this project
requires a multidisciplinary approach and complementary advances in computer science and clinical care.
From the healthcare perspective, this project will offer evidence-based and personalized decision support
to caregivers for better mechanical ventilation weaning. The long-term impact of autonomous mechanical
ventilation weaning pain will lead to shorter hospital stays, reduce the economic burden of health care, and
reduce the deadly side effects of inappropriate weaning.

## Key facts

- **NIH application ID:** 10240657
- **Project number:** 5R01EB029767-03
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** BARRY D FUCHS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $382,956
- **Award type:** 5
- **Project period:** 2019-09-30 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10240657

## Citation

> US National Institutes of Health, RePORTER application 10240657, CPS: AutoWean: Foundations of Autonomous Medical CPS for Mechanical Ventilation Weaning (5R01EB029767-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10240657. Licensed CC0.

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