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|a Wentworth, Adam J
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|a Massachusetts Institute of Technology. Microsystems Technology Laboratories
|e contributor
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|a Massachusetts Institute of Technology. Department of Mechanical Engineering
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|a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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|a Koch Institute for Integrative Cancer Research at MIT
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|a Byrne, James D
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|a Orguc, Sirma
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|a Sands, Joanna
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|a Maji, Saurav
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|a Tov, Caitlynn
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|a Babaee, Sahab
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|a Boyce, Hannah
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|a Huang, Hen-Wei
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|a Chai, Peter
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|a Min, Seokkee
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|a Li, Canchen
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|a Chu, Jacqueline N.
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|a Som, Avik
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|a Becker, Sarah L
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|a Gala, Manish
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|a Chandrakasan, Anantha P
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|a Traverso, Carlo Giovanni
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|a Prospective Evaluation of the Transparent, Elastomeric, Adaptable, Long-Lasting (TEAL) Respirator
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|b American Chemical Society (ACS),
|c 2021-05-12T21:25:50Z.
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|z Get fulltext
|u https://hdl.handle.net/1721.1/130587
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|a N95 filtering facepiece respirators (FFR) and surgical masks are essential in reducing airborne disease transmission, particularly during the COVID-19 pandemic. However, currently available FFR's and masks have major limitations, including masking facial features, waste, and integrity after decontamination. In a multi-institutional trial, we evaluated a transparent, elastomeric, adaptable, long-lasting (TEAL) respirator to evaluate success of qualitative fit test with user experience and biometric evaluation of temperature, respiratory rate, and fit of respirator using a novel sensor. There was a 100% successful fit test among participants, with feedback demonstrating excellent or good fit (90% of participants), breathability (77.5%), and filter exchange (95%). Biometric testing demonstrated significant differences between exhalation and inhalation pressures among a poorly fitting respirator, well-fitting respirator, and the occlusion of one filter of the respirator. We have designed and evaluated a transparent elastomeric respirator and a novel biometric feedback system that could be implemented in the hospital setting.
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|a NIH(Grants K23DA044874, R44DA051106)
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|a NIH (Grants K23DA044874, R44DA051106, 5T32DK007191-4)
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|a en
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|a Article
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|t ACS Pharmacology and Translational Science
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