Screening parameters of pulmonary and cardiovascular integrated model with sensitivity analysis

Previously, we built a pulmonary and cardiovascular integrated model which is driven by O2 consumption. However this model is adjusted to average person and cannot correspond to individual difference. It needs parameter adjustment to be applied for simulation of a particular person. We used lumped parameter models, which have simple structures and are well suited to macro-model. However they have a drawback that the number of parameters becomes large if the model describes organs in detail. Since our model has more than 100 parameters, it is ineffective to estimate all parameters. For efficient parameter tuning, we selected important parameters which have significant influence on outputs with a kind of sensitivity analysis method. The model can be well approximated only by the important parameters.