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Low-cost measurement of facemask efficacy for filtering expelled droplets during speech
2020-08-10 | Since 2 Month

The global spread of COVID-19 in early 2020 has significantly increased the demand for face masks around the world, while stimulating research about their efficacy. Here we adapt a recently demonstrated optical imaging approach (1, 2) and highlight stark differences in the effectiveness of different masks and mask alternatives to suppress the spread of respiratory droplets during regular speech.

In general, the term ‘face mask’ governs a wide range of protective equipment with the primary function of reducing the transmission of particles or droplets. The most common application in modern medicine is to provide protection to the wearer (e.g., first responders), but surgical face masks were originally introduced to protect surrounding persons from the wearer, such as protecting patients with open wounds against infectious agents from the surgical team (3), or the persons surrounding a tuberculosis patient from contracting the disease via airborne droplets (4).
This latter role has been embraced by multiple governments and regulatory agencies (5), since COVID-19 patients can be asymptomatic but contagious for many days (6).
The premise of protection from infected persons wearing a mask is simple: wearing a face mask will reduce the spread of respiratory droplets containing viruses. In fact, recent studies suggest that wearing face masks reduces the spread of COVID-19 on a population level, and consequently blunts the growth of the epidemic curve (7, 8).
Still, determining mask efficacy is a complex topic that is still an active field of research (see for example (9)), made even more complicated because the infection pathways for COVID-19 are not yet fully understood and are complicated by many factors such as the route of transmission, correct fit and usage of masks, and environmental variables.
From a public policy perspective, shortages in supply for surgical face masks and N95 respirators, as well as concerns about their side effects and the discomfort of prolonged use (10), have led to public use of a variety of solutions which are generally less restrictive (such as homemade cotton masks or bandanas), but usually of unknown efficacy. While some textiles used for mask fabrication have been characterized (11), the performance of actual masks in a practical setting needs to be considered. The work we report here describes a measurement method that can be used to improve evaluation in order to guide mask selection and purchase decisions.

A schematic and demonstration image are shown in Fig. 1. In brief, an operator wears a face mask and speaks into the direction of an expanded laser beam inside a dark enclosure. Droplets that propagate through the laser beam scatter light, which is recorded with a cell phone camera. A simple computer algorithm is used to count the droplets in the video.
The required hardware for these measurements is commonly available; suitable lasers and optical components are accessible in hundreds of research laboratories or can be purchased for less than $200, and a standard cell phone camera can serve as a recording device. The experimental setup is simple and can easily be built and operated by non-experts.

Below we describe the measurement method and demonstrate its capabilities for mask testing. In this application, we do not attempt a comprehensive survey of all possible mask designs or a systematic study of all use cases.
We merely demonstrated our method on a variety of commonly available masks and mask alternatives with one speaker, and a subset of these masks were tested with four speakers. Even from these limited demonstration studies, important general characteristics can be extracted by performing a relative comparison between different face masks and their transmission of droplets.


We tested 14 commonly available masks or masks alternatives, one patch of mask material, and a professionally fit-tested N95 mask (see Fig. 2 and Table 1 for details). For reference, we recorded control trials where the speaker wore no protective mask or covering. Each test was performed with the same protocol. The camera was used to record a video of approximately 40 s length to record droplets emitted while speaking.

The first 10 s of the video serve as baseline.
In the next 10 s, the mask wearer repeated the sentence “Stay healthy, people” five times (speech), after which the camera kept recording for an additional 20 s (observation). For each mask and for the control trial, this protocol was repeated 10 times. We used a computer algorithm (see Materials and Methods) to count the number of particles within each video.

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