Uncertainty estimation of output of respiration monitoring system using Monte-Carlo simulations

The paper is focused on the estimation of uncertainty in the measurement of air-flow rate by a piezo sensor as part of a neo-natal respiration monitoring system. The method used for this estimation is the standard Monte-Carlo simulations. The input data is assumed to have a Gaussian frequency distribution. The uncertainty in the measurement is mainly brought about by movement of mechanical parts of the system, random movement of the subject, a spatial lag between the subject´s nose and the sensor strip under certain configurations. The uncertainty in output repeatability of the sensor is neglected. The system aims to reduce the cost of respiration monitoring in neo-nates by using an ultra-cheap piezo sensor. The measurement technique is non-invasive and non-touching, adding value to the system.