Evaluation of a Proportional–Integral–Derivative Controller for Hemorrhage Resuscitation Using a Hardware-in-Loop Test Platform

Abstract

Hemorrhage is a leading cause of preventable death in trauma, which can often be avoided with proper fluid resuscitation. Fluid administration can be cognitive-demanding for medical personnel as the rates and volumes must be personalized to the trauma due to variations in injury severity and overall fluid responsiveness. Thus, automated fluid administration systems are ideal to simplify hemorrhagic shock resuscitation if properly designed for a wide range of hemorrhage scenarios. Here, we highlight the development of a proportional–integral–derivative (PID) controller using a hardware-in-loop test platform. The controller relies only on an input data stream of arterial pressure and a target pressure; the PID controller then outputs infusion rates to stabilize the subject. To evaluate PID controller performance with more than 10 controller metrics, the hardware-in-loop platform allowed for 11 different trauma-relevant hemorrhage scenarios for the controller to resuscitate against. Overall, the two controller configurations performed uniquely for the scenarios, with one reaching the target quicker but often overshooting, while the other rarely overshot the target but failed to reach the target during severe hemorrhage. In conclusion, PID controllers have the potential to simplify hemorrhage resuscitation if properly designed and evaluated, which can be accomplished with the test platform shown here.

An Automated Hardware-in-Loop Testbed for Evaluating Hemorrhagic Shock Resuscitation Controllers

“…As fluid responsiveness is patient-dependent, with a few simple design changes the PhysioVessel system shown here is able to create the different pressure–volume dynamics required to better account for subject variability when designing and testing resuscitation systems. While benchtop controller evaluation cannot replace in vivo testing, it can precede or supplement animal testing in order to narrow down the selection of controller architectures or conduct initial troubleshooting, which can reduce the animal burden [ 17 , 34 ]. The design process for fabricating PhysioVessels is simple, and can be tuned to the end user’s test needs or combined with multiple PhysioVessel shapes to replicate hemorrhage scenarios in which infusate types may need to be swapped, for example due to limited whole blood resources.…”

“…Another key feature of the presented benchtop hemorrhage test platform is automated outflow logic, which together with the effect of the infusate type on capillary interstitial fluid transfer results in a flexible system for which a limitless number of potential hemorrhage scenarios can be devised [ 17 ]. Interstitial fluid transfer from the vasculature was accounted for here with whole-blood and crystalloid PhysioVessel designs [ 20 ].…”

“…To better highlight the utility of the test platform, we have demonstrated an evaluation of a hemorrhage controller with different bleed scenarios in order to detail how critical controller performance metrics can be quantified [ 17 ]. Four scenarios were evaluated: (1) an initial fluid loss with a clotting hemorrhage using whole blood infusate; (2) a rapid loss of blood that stops using whole blood infusate; (3) a rapid loss of blood with bolus vasopressor delivery using whole blood infusate; and (4) rapid loss of blood with ongoing non-clotting hemorrhage using crystalloid infusate.…”

“…When the hemorrhage factor for certain scenarios was increased, the controller’s logic could not reach the target pressure, highlighting the need for evaluating controllers in as wide a range of testing scenarios as possible with the test platform. Lastly, the test platform allows for quantification of a range of control system performance metrics, as have been used in previous work, allowing for head-to-head comparison of controller designs and iterations [ 17 ].…”

“…Algorithms that analyze endpoint data and continuously adapt fluid infusion rates through automated infusion pumps, have been tested in silico [ 9 ], as well as in vivo with various animal and human models [ 10 , 11 ], using a variety of commonly used resuscitation fluids [ 12 ]. These closed-loop controllers range from medical devices containing simple decision tables [ 11 , 13 ] to more sophisticated models such as fuzzy logic [ 11 , 14 , 15 ], proportional integral derivative [ 16 , 17 ], and adaptive controllers [ 9 , 16 , 18 , 19 ].…”