Monitoring multi-respiratory indices via a smart nanofibrous mask filter based on a triboelectric nanogenerator

Respiratory parameters, such as respiratory rate (RR), inhalation time (tin), exhalation time (tex), and their ratio (IER=tin/tex), are of great importance to indicate clinical differences between healthy people and those with respiratory diseases. Herein, we report a respiration monitoring triboelectric nanogenerator (RM-TENG) with nanofibrous membranes, which can be used as a smart, changeable, self-powered mask filter with high filtration efficiency for monitoring multiple respiratory indices (e.g., RR, tin, tex, IER). We created a mathematical model to quantitatively analyze the effects of gap distance between two triboelectric layers on the contact area by recording the nanofibers layer's deformation profile with digital image correlation (DIC) tests. The RM-TENG is more sensitive to smaller gap distances between 1 mm and 5 mm because the high specific area of nanofibers can provide a more effective contact area. An RM-TENG built with optimized structure parameters can accurately and consistently detect the above-mentioned respiratory indices with excellent sensing stability for 40 h. The monitored RR and IER have 100% and 93.53% agreement with the real-time RR and IER set on the ventilator, respectively. Furthermore, it has a filtration efficiency of 99 wt% for particle sizes between 0.3 µm and 5 µm. This study introduces a mask filter fabricated with a simple structure with both filtering and sensing capability, which has excellent potential for self-powered health diagnostics.