Automatic control of arterial blood pressure: computer, benchtop, and animal models
- 1Department of Emergency Medicine, School of Medicine, Duke University , , ,
- 2Pratt School of Engineering, Duke University , , ,
Abstract
Background
Timely, accurate, and stable control of blood pressure (BP) in critical illness is essential for good clinical outcomes. The current clinical standard entails human operators intervening between the monitor and infusion pump, introducing delay, potential error, and risk of over- and undershoot of therapeutic goals. We developed and tested a closed-loop, automatic control system for BP using computer, benchtop, and animal models.Methods
All models employed a proportional-integral-derivative (PID) algorithm to control mean arterial pressure (MAP). The three components are summed to determine the final output, corresponding to the infusion rate of fluids or vasoactive drugs. The computer model simulated an automatically controlled drug infusion to regulate MAP. The benchtop model added physical components (clinical cardiac monitor, microcontroller, medication pump, and pressure transducer), adjusting the hydrostatic pressure in a closed system to meet a target. In the animal model, the MAP of anesthetized swine undergoing surgery was regulated using an automatically controlled norepinephrine or clevidipine infusion. For the animal model, statistical inference and comparison between trials could not be made given the sequential, non-independent design; quantities are descriptive only, not inferential. We applied common control system metrics including rise time, settling time, and on-target percentage (OTP).Results
The computer model rapidly reached and maintained target MAP ± 5 mmHg with OTP of 90% (95% CI 89.4%, 90.6%) at 240 simulated seconds (ss) and 95% (95% CI 94.6%, 95.4%) at 294 ss. The benchtop system reached and maintained target MAP with a mean rise time of 0.47 ± SD 0.15 min, mean settling time of 0.62 ± SD 0.18 min, and mean OTP (using a tolerance of MAP ± 5 mmHg) of 91.25 ± 9.68%. In a swine model, automatic norepinephrine augmented MAP by > 15 mmHg with mean rise time of 2.25 (SD 0.65) min and mean OTP of 56.9% (SD 22.7%). No trial maintained an equilibrium value of target MAP ± 5 mmHg; therefore, no settling time could be calculated. Clevidipine decreased MAP by >15 mmHg with mean rise time of 1.00 (SD 0.40) min, mean settling time of 2.19 (SD 1.45) min, and mean OTP of 93.8% (SD 7.18%). The results of the swine model were confounded by concurrent non-survival surgery. Within this limitation, the swine model demonstrated that the automatic control system was technically feasible.Conclusions
These proof-of-concept studies utilizing computer, benchtop, and animal models provide initial evidence that an automatic PID algorithm has potential to control BP across a range of starting BP. Future studies can optimize the system and compare its performance with human operators in advance of potential human clinical trials.
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BibTeX
@article{sriram2026automatic,
title = {{Automatic control of arterial blood pressure: computer, benchtop, and animal models}},
author = {Raghav Sriram and Bijan Abar and Siri Gullapalli and Yuhe Hu and Akshar Patel and Joshua Seth Broder},
journal = {Frontiers in medical technology},
year = {2026},
month = oct,
doi = {10.3389/fmedt.2026.1955568},
url = {https://europepmc.org/article/PMC/PMC13716810},
note = {CC BY},
}
RIS
TY - JOUR
TI - Automatic control of arterial blood pressure: computer, benchtop, and animal models
AU - Raghav Sriram
AU - Bijan Abar
AU - Siri Gullapalli
AU - Yuhe Hu
AU - Akshar Patel
AU - Joshua Seth Broder
PY - 2026
DA - 2026/10/15
JO - Frontiers in medical technology
DO - 10.3389/fmedt.2026.1955568
UR - https://europepmc.org/article/PMC/PMC13716810
AB - Background Timely, accurate, and stable control of blood pressure (BP) in critical illness is essential for good clinical outcomes. The current clinical standard entails human operators intervening between the monitor and infusion pump, introducing delay, potential error, and risk of over- and undershoot of therapeutic goals. We developed and tested a closed-loop, automatic control system for BP using computer, benchtop, and animal models.Methods All models employed a proportional-integral-derivative (PID) algorithm to control mean arterial pressure (MAP). The three components are summed to determine the final output, corresponding to the infusion rate of fluids or vasoactive drugs. The computer model simulated an automatically controlled drug infusion to regulate MAP. The benchtop model added physical components (clinical cardiac monitor, microcontroller, medication pump, and pressure transducer), adjusting the hydrostatic pressure in a closed system to meet a target. In the animal model, the MAP of anesthetized swine undergoing surgery was regulated using an automatically controlled norepinephrine or clevidipine infusion. For the animal model, statistical inference and comparison between trials could not be made given the sequential, non-independent design; quantities are descriptive only, not inferential. We applied common control system metrics including rise time, settling time, and on-target percentage (OTP).Results The computer model rapidly reached and maintained target MAP ± 5 mmHg with OTP of 90% (95% CI 89.4%, 90.6%) at 240 simulated seconds (ss) and 95% (95% CI 94.6%, 95.4%) at 294 ss. The benchtop system reached and maintained target MAP with a mean rise time of 0.47 ± SD 0.15 min, mean settling time of 0.62 ± SD 0.18 min, and mean OTP (using a tolerance of MAP ± 5 mmHg) of 91.25 ± 9.68%. In a swine model, automatic norepinephrine augmented MAP by > 15 mmHg with mean rise time of 2.25 (SD 0.65) min and mean OTP of 56.9% (SD 22.7%). No trial maintained an equilibrium value of target MAP ± 5 mmHg; therefore, no settling time could be calculated. Clevidipine decreased MAP by >15 mmHg with mean rise time of 1.00 (SD 0.40) min, mean settling time of 2.19 (SD 1.45) min, and mean OTP of 93.8% (SD 7.18%). The results of the swine model were confounded by concurrent non-survival surgery. Within this limitation, the swine model demonstrated that the automatic control system was technically feasible.Conclusions These proof-of-concept studies utilizing computer, benchtop, and animal models provide initial evidence that an automatic PID algorithm has potential to control BP across a range of starting BP. Future studies can optimize the system and compare its performance with human operators in advance of potential human clinical trials.
SN - 2673-3129
ER -