Salman, Naveed, Khan, Muhammad Waqas, Lim, Michael, Khan, Amir, Kemp, Andrew and Noakes, Catherine (2021) Use of Multiple Low Cost Carbon Dioxide Sensors to Measure Exhaled Breath Distribution with Face Mask Type and Wearing Behaviour. Sensors, 21 (18). p. 6204. ISSN 1424-3210
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Abstract
The use of cloth face coverings and face masks has become widespread in light of the COVID-19 pandemic. This paper presents a method of using low cost wirelessly connected carbon dioxide (CO2) sensors to measure the effects of properly and improperly worn face masks on the concentration distribution of exhaled breath around the face. Four types of face masks are used in two indoor environment scenarios. CO2 as a proxy for exhaled breath is being measured with the Sensirion SCD30 CO2 sensor, and data are being transferred wirelessly to a base station. The exhaled CO2 is measured in four directions at various distances from the head of the subject, and interpolated to create spatial heat maps of CO2 concentration. Statistical analysis using the Friedman’s analysis of variance (ANOVA) test is carried out to determine the validity of the null hypotheses (i.e., distribution of the CO2 is same) between different experiment conditions. Results suggest CO2 concentrations vary little with the type of mask used; however, improper use of the face mask results in statistically different CO2 spatial distribution of concentration. The use of low cost sensors with a visual interpolation tool could provide an effective method of demonstrating the importance of proper mask wearing to the public.
Item Type: | Article |
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Additional Information: | Funding information: This work is funded by the UK, EPSRC HECOIRA Project EP/P023312/1. |
Uncontrolled Keywords: | face mask, CO2 sensors, COVID-19, data interpolation |
Subjects: | B900 Others in Subjects allied to Medicine G900 Others in Mathematical and Computing Sciences H900 Others in Engineering |
Department: | Faculties > Engineering and Environment > Mechanical and Construction Engineering |
Depositing User: | Rachel Branson |
Date Deposited: | 13 Sep 2021 10:06 |
Last Modified: | 15 Oct 2021 10:37 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/47143 |
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