A new recursive least-squares procedure for on-line tracking of changes in viscoelastic properties of respiratory mechanics is proposed and applied to artificially ventilated patients. Classical least-squares methods based on simple first-order linear models with time-constant parameters generally provide systematic residuals that hardly satisfy standard statistical tests for model validation in terms of residuals. On the other hand, high order and/or nonlinear models introduce parameters whose estimates are of difficult interpretation in a clinical context. The present procedure overcomes these limitations by using the well-known first-order model of respiratory mechanics, wherein variability of resistance and elastance during the breathing cycle is allowed to take into account nonlinear and high-order behavior. Mean and standard deviation of resistance and elastance estimates, relative to a respiratory cycle, are then determined recursively. Feasibility of the method is evaluated by applying it both to experimental and simulated pressure-airflow signals measured in an intensive care unit during mechanical ventilation of patients recovering from heart surgery. Results demonstrate that the proposed procedure provides data description satisfying statistical tests, such as residual whiteness, and reliable estimates of viscoelastic lung parameters even during substantial and fast variations in the respiratory status. In addition, unlike classical methods, the new technique provides the means for on-line evaluation of parameter variability during each respiratory cycle, by the estimate of their standard deviations. This is important in clinical practice, because only the knowledge of reliable parameter values and standard deviations enables significant changes in the respiratory viscoelastic characteristics, and thus in patient status, to be assessed.