In vivo evaluation of an adaptive resuscitation controller using whole blood and crystalloid infusates for hemorrhagic shock
EJ Snider, SJ Vega, IA Nessen… - … in Bioengineering and …, 2024 - frontiersin.org
Introduction Hemorrhage remains the leading cause of preventable death on the battlefield.
The most effective means to increase survivability is early hemorrhage control and fluid …
The most effective means to increase survivability is early hemorrhage control and fluid …
[HTML][HTML] Data-driven identification and comparison of full multivariable models for propofol–remifentanil induced general anesthesia
In this paper, we present results with clinical data to enable a 2x2 input–output multivariable
patient model for hypnosis and analgesia. Nonlinear multi-drug interaction models are …
patient model for hypnosis and analgesia. Nonlinear multi-drug interaction models are …
Dynamic Estimation of Cardiovascular State From Arterial Blood Pressure Recordings
Real-time estimation of patient cardiovascular states, including cardiac output and systemic
vascular resistance, is necessary for personalized hemodynamic monitoring and …
vascular resistance, is necessary for personalized hemodynamic monitoring and …
Refined Aircraft Positioning Based on Stochastic Hybrid Estimation with Adaptive Square-Root Unscented Particle Filtering
Y Zhang, Z Gao, K Qi, J Li - Aerospace, 2024 - mdpi.com
The positioning of civil aviation aircraft relative to a geographic reference point on Earth in a
Cartesian frame is significant to detect the deviations from the desired path, especially for …
Cartesian frame is significant to detect the deviations from the desired path, especially for …
Model Extraction From Clinical Data Subject to Large Uncertainties and Poor Identifiability
CM Ionescu, R De Keyser, D Copot… - IEEE Control …, 2024 - ieeexplore.ieee.org
This letter presents an extension to system theory as a novel approach to provide models
from clinical data under large uncertainty and poor identifiability conditions. These difficult …
from clinical data under large uncertainty and poor identifiability conditions. These difficult …