Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose

Kobi Snitz, Michal Andelman-Gur, Liron Pinchover, Reut Weissgross, Aharon Weissbrod, Eva Mishor, Roni Zoller, Vera Linetsky, Abebe Medhanie, Sagit Shushan, Eli Jaffe, Noam Sobel

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Rapid diagnosis is key to curtailing the Covid-19 pandemic. One path to such rapid diagnosis may rely on identifying volatile organic compounds (VOCs) emitted by the infected body, or in other words, identifying the smell of the infection. Consistent with this rationale, dogs can use their nose to identify Covid-19 patients. Given the scale of the pandemic, however, animal deployment is a challenging solution. In contrast, electronic noses (eNoses) are machines aimed at mimicking animal olfaction, and these can be deployed at scale. To test the hypothesis that SARS CoV-2 infection is associated with a body-odor detectable by an eNose, we placed a generic eNose in-line at a drive-through testing station. We applied a deep learning classifier to the eNose measurements, and achieved real-time detection of SARS CoV-2 infection at a level significantly better than chance, for both symptomatic and non-symptomatic participants. This proof of concept with a generic eNose implies that an optimized eNose may allow effective real-time diagnosis, which would provide for extensive relief in the Covid-19 pandemic.

Original languageEnglish
Article numbere0252121
JournalPLoS ONE
Volume16
Issue number6 June
DOIs
StatePublished - 1 Jun 2021

ASJC Scopus subject areas

  • General

Fingerprint

Dive into the research topics of 'Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose'. Together they form a unique fingerprint.

Cite this