Optimal Control of Mechanical Ventilators with Learned Respiratory Dynamics

Isaac Ronald Ward, Dylan M. Asmar, Mansur Arief, Jana Krystofova Mike, Mykel J. Kochenderfer
11/12/2024
eess.SYcs.LG

No official code found. Best implementation: sisl/ventilators (3 stars, last commit 2025-07-07).

Abstract

Deciding on appropriate mechanical ventilator management strategies significantly impacts the health outcomes for patients with respiratory diseases. Acute Respiratory Distress Syndrome (ARDS) is one such disease that requires careful ventilator operation to be effectively treated. In this work, we frame the management of ventilators for patients with ARDS as a sequential decision making problem using the Markov decision process framework. We implement and compare controllers based on clinical guidelines contained in the ARDSnet protocol, optimal control theory, and learned latent dynamics represented as neural networks. The Pulse Physiology Engine's respiratory dynamics simulator is used to establish a repeatable benchmark, gather simulated data, and quantitatively compare these controllers. We score performance in terms of measured improvement in established ARDS health markers (pertaining to improved respiratory rate, oxygenation, and vital signs). Our results demonstrate that techniques leveraging neural networks and optimal control can automatically discover effective ventilation management strategies without access to explicit ventilator management procedures or guidelines (such as those defined in the ARDSnet protocol).

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Code for the paper "Optimal Control of Mechanical Ventilators with Learned Respiratory Dynamics"

30PythonMay 22, 20241 years ago

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Cite this paper

@article{ward2024optimal,
  title  = {Optimal Control of Mechanical Ventilators with Learned Respiratory Dynamics},
  author = {Isaac Ronald Ward and Dylan M. Asmar and Mansur Arief and Jana Krystofova Mike and Mykel J. Kochenderfer},
  year   = {2024},
  eprint = {2411.07971},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2411.07971v1}
}

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