An Open Source Mask-based Turbine Spirometer for Respiratory Function Assessment

Spirometry is the most widely used test to evaluate lung function, enabling the diagnosis of respiratory pathologies. Nevertheless, turbine spirometers typically provide limited low-level access to the collected data for computational/research use and have a high cost, reaching thousands of euros. In this work, an open-source, low-cost and user-friendly turbine spirometer is presented. The device is mostly composed of 3D-printed parts and uses simple electronic components. It can be used to assess and characterize respiratory function, based on the inspiration and expiration phases airflow dynamics. Furthermore, in our approach an anesthesia facial mask is used, making the measurements more comfortable for the subjects (when compared to the standard approaches that require nasal clipping to direct all airflow to the mouth). Six trials were performed with low errors in determining respiratory frequency and average inspiratory and expiratory periods, when compared to a reference method, the stopwatch. This work establishes future opportunities for studies seeking the refinement of algorithms devised to obtain the characteristic flow-volume curves of spirometry, which enable the extraction of important respiratory indicators.