A theoretical study of controlled ventilation

Optimal determination of respiratory airflow patterns using a nonlinear multicompartment model for a lung mechanics system

We develop optimal respiratory airflow patterns using a nonlinear multicompartment model for a lung mechanics system. Specifically, we use classical calculus of variations minimization techniques to derive an optimal airflow pattern for inspiratory and expiratory breathing cycles. The physiological interpretation of the optimality criteria used involves the minimization of work of breathing and lung volume acceleration for the inspiratory phase, and the minimization of the elastic potential energy and rapid airflow rate changes for the expiratory phase. Finally, we numerically integrate the resulting nonlinear two-point boundary value problems to determine the optimal airflow patterns over the inspiratory and expiratory breathing cycles.

Closed-loop control for intensive care unit sedation

The potential clinical applications of active control for pharmacology in general, and anesthesia and critical care unit medicine in particular, are clearly apparent. Specifically, monitoring and controlling the depth of anesthesia in surgery and the intensive care unit is of particular importance. Nonnegative and compartmental models provide a broad framework for biological and physiological systems, including clinical pharmacology, and are well suited for developing models for closed-loop control for drug administration. These models are derived from mass and energy balance considerations that involve dynamic states whose values are nonnegative and are characterized by conservation laws (e.g., mass, energy, fluid, etc.) capturing the exchange of material between kinetically homogenous entities called compartments. Compartmental models have been particularly important for understanding pharmacokinetics and pharmacodynamics. One of the basic motivations for pharmacokinetic/pharmacodynamic research is to improve drug delivery. In critical care medicine it is current clinical practice to administer potent drugs that profoundly influence levels of consciousness, respiratory, and cardiovascular function by manual control based on the clinician's experience and intuition. Open-loop control (manual control) by clinical personnel can be tedious, imprecise, time-consuming, and sometimes of poor quality, depending on the skills and judgement of the clinician. Closed-loop control based on appropriate dynamical systems models merits investigation as a means of improving drug delivery in the intensive care unit. In this article, we discuss the challenges and opportunities of feedback control using nonnegative and compartmental system theory for the specific problem of closed-loop control of intensive care unit sedation. Several closed-loop control paradigms are investigated including adaptive control, neural network adaptive control, optimal control, and hybrid adaptive control algorithms for intensive care unit sedation.

Implications of a biphasic two-compartment model of constant flow ventilation for the clinical setting

PURPOSE

To investigate the theoretical effects of changing frequency (f), duty cycle (D), or end-inspiratory pause length on the distribution of ventilation and compartmental pressure in a heterogeneous, two compartment pulmonary model inflated by constant flow.

METHODS

Differential equations governing compartmental volume changes were derived and solved. Validation was conducted in a mechanical lung analogue with two mechanically independent compartments. Model predictions were then generated over wide ranges of f, D, or end-inspiratory pause.

RESULTS

Disparity of compartmental end-expiratory pressure was identified as the primary mechanism by which changes in f, D, or pause alter the distribution of ventilation. Distribution of peak pressures was less sensitive to such changes. Compartmental ventilation was much less uniform than compartmental peak pressure. Ventilation could not be made entirely uniform by changes of f, D, or pause within the usual clinical range.

CONCLUSIONS

In a linear, two compartment model of the respiratory system, disparity of compartmental end-expiratory pressures is the primary mechanism by which changes of f, D, or pause alter the distribution of ventilation during inflation with constant flow. Ventilation is less evenly distributed than peak alveolar pressure, and there are limits to the beneficial effects on the distribution of ventilation to be gained from manipulations of machine settings.

A general mathematical model for respiratory dynamics relevant to the clinical setting

We have developed and validated a general mathematical model for the dynamic behavior of the single-compartment respiratory system in response to an arbitrary waveform of applied inspiratory pressure. Our general model for ventilation applies to all integrable functions of applied pressure, and it enables computation of most ventilation and pressure variables of clinical interest from clinician-selected and impedance-determined inputs readily measured or estimated at the bedside. Interactions between both phases of the ventilatory cycle are considered by assuming that deflation occurs passively from a unicompartment lung. Because this flexible model appears both capable of accurate prediction and robust to major violations of its underlying linear assumptions, it may prove to be of value in a variety of scientific, educational, and clinical settings.

Towards a better classification of lung ventilators

Previous classifications of lung ventilators are discussed with their attendant disadvantages. The need for a new classification is indicated, and a new classification proposed. This classification is based on flow control and force characteristics, together with the peak pressure achieved by the ventilator. Examples are used to illustrate the new classification.