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Supervisory Algorithm for Autonomous Hemodynamic Management Systems.
Snider, Eric J; Vega, Saul J; Ross, Evan; Berard, David; Hernandez-Torres, Sofia I; Salinas, Jose; Boice, Emily N.
Afiliação
  • Snider EJ; Engineering, Technology, and Automation Group, U.S. Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA.
  • Vega SJ; Engineering, Technology, and Automation Group, U.S. Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA.
  • Ross E; Blood and Shock Resuscitation Group, United States Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA.
  • Berard D; Engineering, Technology, and Automation Group, U.S. Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA.
  • Hernandez-Torres SI; Engineering, Technology, and Automation Group, U.S. Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA.
  • Salinas J; Engineering, Technology, and Automation Group, U.S. Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA.
  • Boice EN; Engineering, Technology, and Automation Group, U.S. Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA.
Sensors (Basel) ; 22(2)2022 Jan 11.
Article em En | MEDLINE | ID: mdl-35062489
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Medicina Militar Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Medicina Militar Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos