Supervisory Algorithm for Autonomous Hemodynamic Management Systems.

Eric J Snider,Saul J Vega,Sofia I Hernandez-Torres,Jose Salinas,David Berard,Emily N Boice,Evan Ross

doi:10.3390/s22020529

Eric J Snider, Saul J Vega + Show 5 more

Open Access

https://doi.org/10.3390/s22020529

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Abstract

Future military conflicts will require new solutions to manage combat casualties. The use of automated medical systems can potentially address this need by streamlining and augmenting the delivery of medical care in both emergency and combat trauma environments. However, in many situations, these systems may need to operate in conjunction with other autonomous and semi-autonomous devices. Management of complex patients may require multiple automated systems operating simultaneously and potentially competing with each other. Supervisory controllers capable of harmonizing multiple closed-loop systems are thus essential before multiple automated medical systems can be deployed in managing complex medical situations. The objective for this study was to develop a Supervisory Algorithm for Casualty Management (SACM) that manages decisions and interplay between two automated systems designed for management of hemorrhage control and resuscitation: an automatic extremity tourniquet system and an adaptive resuscitation controller. SACM monitors the required physiological inputs for both systems and synchronizes each respective system as needed. We present a series of trauma experiments carried out in a physiologically relevant benchtop circulatory system in which SACM must recognize extremity or internal hemorrhage, activate the corresponding algorithm to apply a tourniquet, and then resuscitate back to the target pressure setpoint. SACM continues monitoring after the initial stabilization so that additional medical changes can be quickly identified and addressed, essential to extending automation algorithms past initial trauma resuscitation into extended monitoring. Overall, SACM is an important step in transitioning automated medical systems into emergency and combat trauma situations. Future work will address further interplay between these systems and integrate additional medical systems.

Highlights

Because they can automatically execute rapid adjustments in care in response to a patient’s needs, autonomous and semi-autonomous medical systems hold the promise of revolutionizing the practice and delivery of personalized medicine [1,2,3]
Rapid adjustments are critical for patient management in the perioperative and intensive care setting, where closed-loop controllers have been developed for ventilator management [4,5,6]
The supervisory algorithm we describe here can recognize a simulated hemorrhage by sensing the loss of system pressure, activate a closed-loop tourniquet controller, and activate a closed-loop resuscitation algorithm to return the system to an arterial pressure setpoint

Summary

Introduction

Because they can automatically execute rapid adjustments in care in response to a patient’s needs, autonomous and semi-autonomous medical systems hold the promise of revolutionizing the practice and delivery of personalized medicine [1,2,3]. As is often the case in the perioperative setting [13] and the intensive care unit [14,15], when a patient requires multiple interventions simultaneously the clinician will prioritize one line of treatment at the expense of anotherin such a hypothetical situation in which two autonomous systems would be at odds, each algorithm lacks the ability to adjust its own performance to meet the needs of the other, potentially leading to catastrophic unintended consequences. Successful integration of multiple closed-loop systems, requires that the medical delivery team be capable of harmonizing the performance of the controllers to the benefit of the patient and adjudicating between the controllers when they conflict

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Results

Conclusion