Fleur T. Tehrani

A mathematical model of the human respiratory system

A model of the human respiratory system is proposed which has a satisfactory performance under different physiological conditions. The model comprises a continuous plant and a discrete controller which generates and updates the drive signal to the plant at the end of every breath to represent the Hering-Breuer reflex. Arterial and central medullary sensors are included. The lung volume, dead space volume, cardiac output and cerebral blood flow are time varying. The respiratory work is minimized. The model is examined and simulation results of its performance in hypercapnia, hypoxia, periodic breathing and moderate exercise are presented. The responses presented include the relatively fast transients of Cheyne-Stokes breathing and the slower transients associated with carbon dioxide inhalation.

A dual closed-loop control system for mechanical ventilation.

Objective. Closed-loop mechanical ventilation has the potential to provide more effective ventilatory support to patients with less complexity than conventional ventilation. The purpose of this study was to investigate the effectiveness of an automatic technique for mechanical ventilation. Methods. Two closed-loop control systems for mechanical ventilation are combined in this study. In one of the control systems several physiological data are used to automatically adjust the frequency and tidal volume of breaths of a patient. This method, which is patented under US Patent number 4986268, uses the criterion of minimal respiratory work rate to provide the patient with a natural pattern of breathing. The inputs to the system include data representing CO2 and O2 levels of the patient as well as respiratory compliance and airway resistance. The I:E ratio is adjusted on the basis of the respiratory time constant to allow for effective emptying of the lungs in expiration and to avoid intrinsic positive end expiratory pressure (PEEP). This system is combined with another closed-loop control system for automatic adjustment of the inspired fraction of oxygen of the patient. This controller uses the feedback of arterial oxygen saturation of the patient and combines a rapid stepwise control procedure with a proportional-integral-derivative (PID) control algorithm to automatically adjust the oxygen concentration in the patients inspired gas. The dual closed-loop control system has been examined by using mechanical lung studies, computer simulations and animal experiments. Results. In the mechanical lung studies, the ventilation controller adjusted the breathing frequency and tidal volume in a clinically appropriate manner in response to changes in respiratory mechanics. The results of computer simulations and animal studies under induced disturbances showed that blood gases were returned to the normal physiologic range in less than 25 s by the control system. In the animal experiments under steady-state conditions, the maximum standard deviations of arterial oxygen saturation and the end-tidal partial pressure of CO2 were ± 1.76% and ± 1.78 mmHg, respectively. Conclusion. The controller maintained the arterial blood gases within normal limits under steady-state conditions and the transient response of the system was robust under various disturbances. The results of the study have showed that the proposed dual closed-loop technique has effectively controlled mechanical ventilation under different test conditions.

Mathematical analysis and computer simulation of the respiratory system in the newborn infant

A mathematical model of neonatal respiratory control which can be used to simulate the system under different physiological conditions is proposed. The model consists of a continuous plant and a discrete controller. Included in the plant are lungs, body tissue, brain tissue, a cerebrospinal fluid compartment, and central and peripheral receptors. The effect of shunt in the lungs is included in the model, and the lung volume and the dead space are time varying. The controller utilizes outputs from peripheral and central receptors to adjust the depth and rate of breathing, and the effects of prematurity of peripheral receptors are included in the system. Hering-Breuer-type reflexes are embodied in the controller to accomplish respiratory synchronization. The model is examined and its simulation results under test conditions in hypoxia and hypercapnia are presented.<<ETX>>

Methodological review: Intelligent decision support systems for mechanical ventilation

OBJECTIVE An overview of different methodologies used in various intelligent decision support systems (IDSSs) for mechanical ventilation is provided. The applications of the techniques are compared in view of todays intensive care unit (ICU) requirements. METHODS Information available in the literature is utilized to provide a methodological review of different systems. RESULTS Comparisons are made of different systems developed for specific ventilation modes as well as those intended for use in wider applications. The inputs and the optimized parameters of different systems are discussed and rule-based systems are compared to model-based techniques. The knowledge-based systems used for closed-loop control of weaning from mechanical ventilation are also described. Finally, in view of increasing trend towards automation of mechanical ventilation, the potential utility of intelligent advisory systems for this purpose is discussed. CONCLUSIONS IDSSs for mechanical ventilation can be quite helpful to clinicians in todays ICU settings. To be useful, such systems should be designed to be effective, safe, and easy to use at patients bedside. In particular, these systems must be capable of noise removal, artifact detection and effective validation of data. Systems that can also be adapted for closed-loop control/weaning of patients at the discretion of the clinician, may have a higher potential for use in the future.

A feedback controller for supplemental oxygen treatment of newborn infants: a simulation study

A microcomputer control system has been developed for supplemental oxygen therapy of newborn infants. The system uses feedback of arterial oxygen saturation to adjust the concentration of oxygen in the incubator or under the hood. The control system has been tested under different physiological conditions, using a detailed simulation model of the neonatal respiratory system. Some of the simulation results of this study are presented to illustrate the performance of the controller.

Automatic control of mechanical ventilation. Part 2: the existing techniques and future trends.

ObjectiveThe major automatic techniques that are available in commercial ventilators are described and a discussion of the recently developed systems along with the future trends in the field is provided.MethodsThe major available automatic control techniques for mechanical ventilation are analyzed and the future trends are discussed in view of today’s ICU requirements and the recently developed technologies.ResultsSeveral major automatic techniques are available in commercial ventilators at this time. Those techniques have been in use successfully and are accepted by clinicians. At the same time, more advanced techniques have been and continue to be developed by various researchers that are designed for more aggressive use of automation in control of ventilation and oxygenation in different phases of ventilatory treatment.ConclusionsAutomatic control of mechanical ventilation can significantly improve patient care in the ICUs, reduce the mortality and morbidity rates associated with provision of inappropriate ventilatory treatments, and reduce healthcare costs. Development of more effective and robust systems that can have high noise immunity and provide effective treatment to patients automatically in different phases of treatment will likely gain increasing momentum in the years to come.

Closed-Loop Control of 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. Conclusion.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.

A microcomputer oxygen control system for ventilatory therapy.

A computer-based feedback system has been developed to adjust the concentration of oxygen in the inspired gas of a patient under artificial respiration. The system uses a proportional plus integral controller and feedback of arterial oxygen saturation to adjust the inspired oxygen fraction. The effectiveness of the controller has been tested using a dynamic, mathematical model of the human respiratory system. This relatively sophisticated model has been developed and examined in the past, and it has been shown that it can realistically describe the human respiratory system for a wide variety of test conditions. The performance of the oxygen control system has been evaluated using the simulation model. The response of the controller to different disturbances is always stable, with arterial pressure of oxygen returning to normal in less than 12 minutes. Some of the simulation results are presented to illustrate the dynamic behavior and robustness of the controller.

Automatic Control of Mechanical Ventilation. Part 1: Theory and History of the Technology

ObjectiveIn this article, automatic control technology as applied to mechanical ventilation is discussed and the techniques that have been reported in the literature are reviewed.MethodsThe information in the literature is reviewed and various techniques are compared.ResultsAutomatic control has been applied in many ways to mechanical ventilation since several decades ago. More aggressive techniques aimed at automatic and more optimal control of the main outputs of the machine have emerged and continue to be enhanced with time.ConclusionsDevelopment of more efficient automatic techniques and/or enhancement of the present methods are likely to be pursued to make this technology more compatible with future healthcare requirements.

On the regulation of cardiac output and cerebral blood flow

Algebraic presentations are used to describe the steady-state relationships for cardiac output and cerebral blood flow in terms of arterial blood levels of oxygen and carbon dioxide and the metabolic rate ratio. A possible application of the results is briefly discussed with regard to their use in modelling of the respiratory control system.