A model for estimation of the pulmonary capillary pressure

To estimate the pulmonary capillary pressure, a theory was introduced by Holloway and coworkers. Based upon this, a mathematical model describing the measured data was developed. Because the physiologic data are embedded in noise and the pulmonary capillary pressure cannot be measured directly, we simulated an extensive series of data. The noise properties of the data were as analyzed to design a signal-processing tool, that cancels the noise from the measured data. The signal processing tool developed for the current application consists of pre-processing with a moving time average filter and post-processing with a neural network. After a verification procedure the tool can be applied to measured data, hence a more reliable measurement of the pulmonary capillary pressure is achieved.