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.