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VeriMask: Sensor Platform for Decontamination of N95 Masks

Published: 25 July 2022 Publication History
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  • Abstract

    In response to the mask shortage during the first wave of the COVID-19 pandemic, we developed an open-source wireless sensor platform, VeriMask, to facilitate per-mask verification of the moist-heat decontamination process for N95 masks. The aim of VeriMask was to enable safe, easy, and accessible moist-heat decontamination in underresourced facilities to protect frontline healthcare workers by lowering their risk of infection from reused N95 masks. In this article we will introduce the VeriMask platform, challenges we encountered in this emergency-response design, design criteria, and lessons learned from our interactions with clinical and near-clinical partners. We hope to raise attention as to how society can be better prepared against future pandemics and other forms of crises by leveraging the expertise of the mobile computing, trustworthy computing, and medical communities.

    References

    [1]
    Yan Long, Alexander Curtiss, Sara Rampazzi, Josiah Hester, and Kevin Fu. 2021. VeriMask: Facilitating decontamination of N95 masks in the Covid-19 pandemic: Challenges, lessons learned, and safeguarding the future. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, no. 3, 1--29.
    [2]
    American Nurses Association. 2020. Updates on nurses and PPE: Survey reveals alarming conditions. https://www.nursingworld. org/~4a558d/globalassets/covid19/ana-ppesurvey- one-pager--final.pdf.
    [3]
    Jerry T.J. Ju, Leah N. Boisvert, and Yi Y. Zuo. 2021. Face masks against COVID-19: Standards, efficacy, testing and decontamination methods. Advances in Colloid and Interface Science, 292: 102435.
    [4]
    Kachorn Seresirikachorn, Vorakamol Phoophiboon, Thitiporn Chobarporn, Kasenee Tiankanon, Songklot Aeumjaturapat, Supinda Chusakul, and Kornkiat Snidvongs. 2021. Decontamination and reuse of surgical masks and N95 filtering facepiece respirators during the COVID-19 pandemic: A systematic review. Infection Control & Hospital Epidemiology, 42, no. 1, 25--30.
    [5]
    Lucia Corsini, Valeria Dammicco, and James Moultrie. 2020. Critical factors for implementing open source hardware in a crisis: Lessons learned from the Covid-19 Pandemic. Journal of Open Hardware, 4, 1.
    [6]
    David Rempel. 2020. Scientific collaboration during the Covid-19 pandemic: N95DECON.org. Annals of Work Exposures and Health

    Cited By

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    • (2023)MANAGERIAL DECISION-MAKING IN THE CONDITIONS OF DIGITALIZATION OF HEALTHCAREЭкономика и предпринимательство10.34925/EIP.2023.154.5.225(1127-1130)Online publication date: 1-Jul-2023

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    Published In

    cover image GetMobile: Mobile Computing and Communications
    GetMobile: Mobile Computing and Communications  Volume 26, Issue 2
    June 2022
    34 pages
    ISSN:2375-0529
    EISSN:2375-0537
    DOI:10.1145/3551670
    Issue’s Table of Contents
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 25 July 2022
    Published in SIGMOBILE-GETMOBILE Volume 26, Issue 2

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    • (2023)MANAGERIAL DECISION-MAKING IN THE CONDITIONS OF DIGITALIZATION OF HEALTHCAREЭкономика и предпринимательство10.34925/EIP.2023.154.5.225(1127-1130)Online publication date: 1-Jul-2023

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