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We consider the problem of tracking rapid changes in the viscous and elastic properties of the respiratory system by using mouth flow and transpulmonary pressure data measured during mechanical ventilation. A recursive least-squares algorithm with adjustable compensator is used for online estimation of an R-C model of the breathing mechanics. Specific simulation experiments are presented to provide guidelines to select suitable values for the key variable, which controls the compromise between tracking ability and noise sensitivity. The results obtained confirm the critical role of the optimum tuning in relation to the noise level. Experimental results obtained from data measured on mechanically-ventilated dogs, in which respiratory distress syndrome was intravenously induced by oleic acid, demonstrate that the tuned algorithm is able to track appropriately both the viscous and elastic properties of lung mechanics. Parameter estimates are consistent with those obtained by standard and robust offline algorithms and their time course is in qualitative agreement with known physiopathological behaviour.

Respiratory treatment involves clinical problems which are often related to the pulmonary and circulatory condition of the patient. Choice of a proper respirator and its adequate use are very important for overcoming a good deal of the clinical problems which may arise. A good automatic ventilator should, under all circumstances, be capable of assuring a suitable gas exchange at the pulmonary level with as little alteration as possible to the physiological functions of the body. In this paper a non-linear model of the mechanics of breathing is used to examine: (1) the effects of four theoretical inspiratory flow patterns in intermittent positive pressure ventilation (IPPV); (2) the differences obtained with respect to IPPV when we use a positive end-expiratory pressure (PEEP) or a negative pressure in the expiratory phase (IPNPV); (3) the performances of four automatic ventilators at present on the market and commonly used in departments of anaesthesia and intensive care. The results obtained by simulation of the respiratory system indicate that, in practice, an ideal ventilator neither exists nor can be designed. The manner of using the ventilator leads to different results, more so than the theoretical inspiratory flow pattern or the type of ventilator used. The tables and graphs shown in the paper help to utilize the ventilator in such a way as to optimize the parameters which, each time, are considered the most important.

In this paper a respiratory mechanics model is considered, which is characterized by a biquadratic input impedance, and a sensitivity analysis has been carried out to determine the influence of experimental conditions on parameter estimation. This analysis was effected with data obtained experimentally, in three different patients under intermittent positive pressure ventilation. In all three cases, the model's input impedance demonstrated a maximum sensitivity in relation to the various parameters included in the field of frequencies from 0 to 10 Hz. This seems to suggest therefore, that the use of a low-pass filter with a cut-off frequency equal to 10 Hz could improve the signal/noise ratio and, consequently, the accuracy of the estimation of the parameters. Furthermore, the use of a system input with a bandwidth of 0-10 Hz provides the experimental conditions, under which good estimates of the parameters can be obtained. This conclusion has also been confirmed by simulation studies which have been conducted with different types of input signals.

In this study, the accuracy achievable in the parameter estimates of a three-element linear model for the systemic vascular bed is considered. The model neglects inertial effects and includes only three elements representing arterial compliance, peripheral resistance and venous compliance, in agreement with recent sensitivity investigations. Parameter estimation starts from arterial and right atrial pressure signals generated by a closed-loop simulator of the cardiovascular circulation and corrupted with normal noise to account for measurement errors. In this way, the influences of a wide variety of circulatory conditions were investigated. The results achieved give evidence that arterial compliance is generally well estimated, while venous compliance is more variable, particularly at high peripheral resistance when measured signals appear to be less sensitive to this parameter. However, presence of cardiac disease, such as heart failure and valvular stenosis has minimal influence on compliance estimates. These results suggest that this simple model can be conveniently applied even under noisy conditions.

A sensitivity analysis study has been performed on a seven-parameter model of the systemic vascular bed in order to obtain structure reductions appropriate for simulation and estimation. This analysis considers separately the systolic and diastolic transfer functions between arterial and venous pressures in order to divide a non-linear problem in two distinct linear problems. The results obtained refer to nominal parameter values corresponding to normal circulatory conditions in man and supply guide-lines for an application-oriented selection of reduced models. Simple resistance-compliance models are preferred because the inertial effects appear to have only slight influence. In particular, the choice of a five-parameter model seems to be convenient for simulation purposes. An additional structure reduction is suggested to reach reliable results in parameter estimation problems. The resulting model is characterized by three elements: peripheral resistance, arterial compliance and venous compliance.