Face masks are required in many occupational settings, and the recent COVID-19 pandemic emergency has created an unprecedented use of this personal protective equipment. In this scenario, smart solutions embedded within the face mask that can monitor physiological parameters may benefit different applications. Respiratory rate (RR) is important among many physiological parameters due to its sensitivity to various physiological and physical stress conditions. In this paper, we designed and developed a smart face mask (SFM) to monitor RR. The system is based on the detection of the different temperatures between inspired and expired gases. Two thermistors embedded within a commercial face mask carry this detection. A custom electronic circuit allows transducing temperature changes into a voltage signal, and a custom algorithm estimates this voltage. The feasibility assessment of the SFM for estimating RR has been performed by comparing the results found on 6 healthy volunteers with the reference Zephyr™ BioHarness. The SFM showed promising results in different respiratory conditions (quiet breathing-QB, tachypnea), with a maximum mean RR difference of 0.18 bpm in QB and 0.49 bpm in tachypnea. The maximum mean absolute percentage error was 4.29% in the QB stage and 4.20% in tachypnea. Further experiments will be performed under more challenging scenarios (e.g., by simulating movements related to sports activities, occupational settings, or clinical procedures. This solution may be considered a first effort in designing, assessing, and optimizing a thermistor-based SFM improvement.
An innovative smart face mask for the estimation of respiratory rate: design, development and feasibility assessment
Giorgi L.;Massaroni C.;Romano C.;Moffa A.;Casale M.;Schena E.
2023-01-01
Abstract
Face masks are required in many occupational settings, and the recent COVID-19 pandemic emergency has created an unprecedented use of this personal protective equipment. In this scenario, smart solutions embedded within the face mask that can monitor physiological parameters may benefit different applications. Respiratory rate (RR) is important among many physiological parameters due to its sensitivity to various physiological and physical stress conditions. In this paper, we designed and developed a smart face mask (SFM) to monitor RR. The system is based on the detection of the different temperatures between inspired and expired gases. Two thermistors embedded within a commercial face mask carry this detection. A custom electronic circuit allows transducing temperature changes into a voltage signal, and a custom algorithm estimates this voltage. The feasibility assessment of the SFM for estimating RR has been performed by comparing the results found on 6 healthy volunteers with the reference Zephyr™ BioHarness. The SFM showed promising results in different respiratory conditions (quiet breathing-QB, tachypnea), with a maximum mean RR difference of 0.18 bpm in QB and 0.49 bpm in tachypnea. The maximum mean absolute percentage error was 4.29% in the QB stage and 4.20% in tachypnea. Further experiments will be performed under more challenging scenarios (e.g., by simulating movements related to sports activities, occupational settings, or clinical procedures. This solution may be considered a first effort in designing, assessing, and optimizing a thermistor-based SFM improvement.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.