A NEW APPROACH FOR TRACKING RESPIRATORY MECHANICAL PARAMETERS IN REAL-TIME

A new recursive least-squares procedure for on-line tracking of change s in viscoelastic properties of respiratory mechanics is proposed and applied to artificially ventilated patients. Classical least-squares m ethods based on simple first-order linear models with time-constant pa rameters generally provide systematic residuals that hardly satisfy st andard statistical tests for model validation in terms of residuals. O n the other hand, high order and/or nonlinear models introduce paramet ers whose estimates are of difficult interpretation in a clinical cont ext. The present procedure overcomes these limitations by using the we ll-known first-order model of respiratory mechanics, wherein variabili ty of resistance and elastance during the breathing cycle is allowed t o take into account nonlinear and high-order behavior. Mean and standa rd deviation of resistance and elastance estimates, relative to a resp iratory cycle, are then determined recursively. Feasibility of the met hod is evaluated by applying it both to experimental and simulated pre ssure-airflow signals measured in an intensive care unit during mechan ical ventilation of patients recovering from heart surgery. Results de monstrate that the proposed procedure provides data description satisf ying statistical tests, such as residual whiteness, and reliable estim ates of viscoelastic lung parameters even during substantial and fast variations in the respiratory status. In addition, unlike classical me thods, the new technique provides the means for on-line evaluation of parameter variability during each respiratory cycle, by the estimate o f their standard deviations. This is important in clinical practice, b ecause only the knowledge of reliable parameter values and standard de viations enables significant changes in the respiratory viscoelastic c haracteristics, and thus in patient status, to be assessed.