Nonlinear curve fitting improves noise sensitivity of the single-breath method for estimation of cardiac output

In a recent theoretical study, Srinivasan (10) presented a new nonlinear curve fitting algorithm for computing pulmonary blood flow by the single-breath method. The results obtained with the new algorithm showed a considerably lower sensitivity of the estimated pulmonary blood flow to experimental noise than with the linear curve fitting technique reported previously by Grønlund (5). In the present study, we have compared the linear and the nonlinear algorithms using computer simulations and experimental single-breath data. The results showed only a small difference between the two methods. Further, we showed that the difference between the noise sensitivities obtained by Grønlund (5) and Srinivasan (10) can be explained almost entirely by a difference between the models used to simulate experimental noise.