Closed-loop control if the inspired fraction of oxygen in mechanical ventilation.
OBJECTIVE
Supplemental oxygen treatment of patients on mechanical ventilation is crucial in maintaining the patients' oxygen levels in the normal range. The purpose of this study was to evaluate the effectiveness of a closed-loop controller for automatic adjustment of the fraction of inspired oxygen, FIO2. More specifically, the aim of the study was to assess the robustness of the controller in correcting hypoxemia as well as its effectiveness in prevention of hyperoxemia and oxygen toxicity.


METHODS
The microprocessor-based feedback control system combines a rapid control algorithm with a proportional-integral-derivative (PID) control procedure to automatically adjust FIO2. The system is designed to prevent hypoxemia by applying a stepwise control procedure in response to rapid declines in arterial oxygen saturation while fine-tuning FIO2 and avoiding hyperoxemia by resuming to the PID control procedure when appropriate. The system includes a sophisticated safeguard unit which is designed to communicate any oxygenation problems or measurement artifacts to the medical personnel while keeping FIO2 at a safe and sufficiently high level. The control system has been tested by using computer simulations as well as animal studies.


RESULTS
In response to different disturbances, the arterial oxygen saturation returned to the normal safe range within less than 20 seconds, thereby avoiding any untoward effects of hypoxemia. Under steady state conditions, the variations in arterial oxygen saturation were kept within +/- 3% of the mean value. The controller corrected hypoxemia within seconds while preventing hyperoxemia, rejecting artifacts, and minimizing exposure to high concentrations of oxygen.


CONCLUSIONS
The results of the study attest to the reliability of the proposed closed-loop control scheme for automatic adjustment of FIO2. Further evaluation of the controller will require testing the effectiveness of the system on different patient groups.
Tehrani
Fleur
F
Department of Electrical Engineering, California State University, Fullerton, California 92834-6870, USA. ftehrani@fullerton.edu
Rogers
Mark
M
Lo
Takkin
T
Malinowski
Thomas
T
Afuwape
Samuel
S
Lum
Michael
M
Grundl
Brett
B
Terry
Michael
M
D000465:Algorithms; D001331:Automation; D003198:Computer Simulation; D006801:Humans; D000860:Hypoxia; D009716:Numerical Analysis, Computer-Assisted; D010092:Oximetry; D010100:Oxygen / Q000097:blood*; D010102:Oxygen Inhalation Therapy; D012016:Reference Values; D012121:Respiration, Artificial
D010100:Oxygen