The conventional pulmonary function tests are based on spirometry, which
unfortunately doesn't produce accurate and reproducible results if performed
without the supervision of specially trained staff. We recently showed that
forced oscillation technique is best suited for the home-monitoring of
respiratory patients.
The aim of this study was to develop a real-time data processing algorithm for
the automatic unsupervised assessment of the lung obstruction, a network
architecture for the data transmission and a web-based application for the
storage and management of the data.
The results demonstrated a high reliability of the algorithm, the robustness of
the data communication protocols and the effectiveness of the data
management web portal.
In conclusion, our system allows a reliable automatic home monitoring of lung
obstruction and it may improve the efficacy and efficiency of the management of
respiratory patients through an improved tailoring of the clinical treatments and
an early detection of exacerbations.
