Abstract
In this paper, we describe a computational model dedicated to building an apnoea monitoring system for newborn babies. The proposed model is based on whole body plethysmography, which involves non-invasive measurement of lung ventilation indirectly from the pressure deflections generated when a subject breathes inside a chamber of fixed volume (Bert in C R Soc Biol Paris 20:22–23, 1868). The computational model simulates thermal and environmental flow conditions occurring in the neonate chamber, especially steady state flow with heat transfer and carbon dioxide (CO2) transport during the exhalation phase. This permits the variance of all critical parameters and the analysis of their effects on the distributions of interest. The main objective is to study thermal and air quality comfort conditions under which infants can be monitored for long-term periods. The method deploys computational fluid dynamics techniques and parametric modelling which, by allowing input parameters to be modulated, represent a more efficient and flexible analytical tool than previous experimental techniques. Simulation data reveal that the largest flow rates occur in areas near the openings with slight formation of air recirculation zones; temperature distribution shows signs of stratification, with higher temperatures than the supplied air, CO2 distribution presents acceptable air quality level and predicted mean vote index affords a relatively acceptable thermal comfort level. This analytical approach can be considered as innovative, and can find a new application in clinical infant apnoea monitoring in a way that allows determination of the optimal location for placing a sensor to detect respiration activity without any contact with the infant’s body, and without any risk, in contrast to available whole body plethysmography techniques previously tested in infants (Fleming et al. in J Appl Physiol 55:1924–1931, 1983).
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Amezzane, I., Awada, A., Sawan, M. et al. Modelling and simulation of an infant’s whole body plethysmograph. Med Bio Eng Comput 44, 823–828 (2006). https://doi.org/10.1007/s11517-006-0068-7
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DOI: https://doi.org/10.1007/s11517-006-0068-7