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Development and Characterization of a Self-Tightening Tourniquet System.

Saul J VegaSofia I Hernandez-TorresDavid BerardEmily N BoiceEric J Snider
Published in: Sensors (Basel, Switzerland) (2022)
Uncontrolled hemorrhage remains a leading cause of death in both emergency and military medicine. Tourniquets are essential to stopping hemorrhage in these scenarios, but they suffer from subjective, inconsistent application. Here, we demonstrate how tourniquet application can be automated using sensors and computer algorithms. The auto-tourniquet self-tightens until blood pressure oscillations are no longer registered by the pressure sensor connected to the pneumatic pressure cuff. The auto-tourniquet's performance in stopping the bleed was comparable to manual tourniquet application, but the time required to fully occlude the bleed was longer. Application of the tourniquet was significantly smoother, and less variable, for the automatic tourniquet compared to manual tourniquet application. This proof-of-concept study highlights how automated tourniquets can be integrated with sensors to provide a much more consistent application and use compared to manual application, even in controlled, low stress testing conditions. Future work will investigate different sensors and tourniquets to improve the application time and repeatability.
Keyphrases
  • blood pressure
  • machine learning
  • deep learning
  • emergency department
  • public health
  • climate change
  • high throughput
  • type diabetes
  • heart rate
  • depressive symptoms
  • low cost
  • insulin resistance
  • working memory
  • weight loss