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Wearing masks is crucial to preventing the spread of potentiallypathogen-containing droplets, especially amidst the COVID-19 pandemic. However,not all face coverings are equally effective and most experiments evaluatingmask efficacy are very expensive and complex to operate. In this work, a novel,home-built, low-cost, and accurate metrology to visualize orally-generatedfluid droplets has been developed. The project includes setup optimization,data collection, data analysis, and applications. The final materials chosenwere quinine-containing tonic water, 397-402 nm wavelength UV tube lights, aniPhone and tripod, string, and a spray bottle. The experiment took place in adark closet with a dark background. During data collection, the test subjectfirst wets their mouth with an ingestible fluorescent liquid (tonic water) andspeaks, sneezes, or coughs under UV darklight. The fluorescence from the tonicwater droplets generated can be visualized, recorded by an iPhone 8+ camera inslo-mo (240 fps), and analyzed. The software VLC is used for frame separationand Fiji/ImageJ is used for image processing and analysis. The dependencies oforal fluid droplet generation and propagation on different phonics, theloudness of speech, and the type of expiratory event were studied in detail andestablished using the metrology developed. The efficacy of different types ofmasks was evaluated and correlated with fabric microstructures. All masksblocked droplets to varying extent. Masks with smaller-sized pores and thickermaterial were found to block the most droplets. This low-cost technique can beeasily constructed at home using materials that total to a cost of less than$50. Despite the minimal cost, the method is very accurate and the data isquantifiable.

A Novel Home-Built Metrology to Analyze Oral Fluid Droplets and Quantify the Efficacy of Masks