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PES and VB were also fitted by the sigmoid regression (Figure 103B shows a sample curve) and the optimal VB was predicted by zero (PES-b).
All V MIN and V MAX determined by the sigmoid regression were within the intermediate linear section obtained by visually inspecting the balloon pressure-volume curve (Additional file 3: Table S2).
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The sigmoid regression function that fits these curves is given by the equation: = a 1 + e x – x o b, where ' a' is the slope of the curve.
Fig. 2 An example of the fitted balloon volume-pressure curve using the sigmoid regression equation.
The overall goodness-of-fit of the sigmoid regression and the accuracy of the balloon volume estimation were assessed.
In the balloon pressure-volume curve analysis, the best-fit coefficient R 2 and the bias-corrected Akaike information criterion (AICc) of the sigmoid regression were calculated [22].
(2) The sigmoid regression fits the balloon pressure-volume curve excellently and enables an accurate estimation of the optimal balloon volume.
Together, these results indicate that the sigmoid regression of balloon pressure and volume can be used to accurately estimate the optimal filling volume.
The balloon pressure-volume curve was fitted by sigmoid regression, and the minimal and maximal balloon volume accurately reflecting the surrounding pressure was estimated using the lower and upper inflection point of the fitted sigmoid curve.
Balloon pressure-volume was fitted by a sigmoid regression: VB = a/[1 + e- P-b /c ], whe- P-b /che- P-b /cl distance of the upper asymptote, b = the pressure at the midpoint between zero and a, and c = the pressure range with the greatest volume change (Figure 103A shows a sample curve).
The balloon pressure-volume curve is fitted well by sigmoid regression and provides an accurate estimation of the balloon volume.
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