BACKGROUND: New-generation ventilators display dynamic measures of respiratory mechanics, such as compliance, resistance, and auto-PEEP. Knowledge of the respiratory mechanics is paramount to clinicians at the bedside. These calculations are obtained automatically by using the least squares fitting method of the equation of motion. The accuracy of these calculations in static and dynamic conditions have not been fully validated or examined in different clinical conditions or various ventilator modes. METHODS: A bench study was performed by using a lung simulator to compare the ventilator automated calculations during passive and active conditions. Three clinical scenarios (normal, COPD, and ARDS) were simulated with known compliances and resistance set per respective condition: normal (compliance 50 mL/cm H 2 O, resistance 10 cm H 2 O/L/s), COPD (compliance 60 mL/cm H 2 O, resistance 22 cm H 2 O/L/s), and ARDS (compliance 30 mL/cm H 2 O, and resistance 13 cm H 2 O/L/s). Each scenario was subjected to 4 different muscle pressures (P mus): 0, ؊5, ؊10, and ؊15 cm H 2 O. All the experiments were done using adaptive support ventilation. The resulting automated dynamic calculations of compliance and resistance were then compared based on the clinical scenarios. RESULTS: There was a small bias (average error) and level of agreement in the passive conditions in all the experiments; however, these errors and levels of agreement got progressively higher proportional to the increased P mus. There was a strong positive correlation between P mus and compliance measured as well as a strong negative correlation between P mus and resistance measured. CONCLUSIONS: Automated displayed calculations of respiratory mechanics were not dependable or accurate in active breathing conditions. The calculations were clinically more reliable in passive conditions. We propose different methods of calculating P mus , which, if incorporated into the calculations, would improve the accuracy of respiratory mechanics made via the least squares fitting method in actively breathing conditions.