Malodour classification with low-cost flexible electronics

Understanding body malodour in a measurable manner is essential for developing personal care products. Body malodour is the result of bodily secretion of a highly complex mixture of volatile organic compounds. Current body malodour measurement methods are manual, time consuming and costly, requiring...

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Bibliographic Details
Published in:Nature communications 2023-02, Vol.14 (1), p.777-777, Article 777
Main Authors: Ozer, Emre, Kufel, Jedrzej, Biggs, John, Rana, Anjit, Rodriguez, Francisco J., Lee-Clark, Thomas, Sou, Antony, Ramsdale, Catherine, White, Scott, Garlapati, Suresh Kumar, Valliappan, Palaniappan, Rahmanudin, Aiman, Komanduri, Venuskrishnan, Saez, Glenn Sunley, Gollu, Sankara, Brown, Gavin, Dudek, Piotr, Persaud, Krishna C., Turner, Michael L., Murray, Stephanie, Bates, Susan, Treloar, Robert, Newby, Brian, Ford, Jane
Format: Article
Language:English
Subjects:
639/166/898
639/166/987
Classification
Consumer products
Electronic noses
Electronics
Flexible components
Hardware
Humanities and Social Sciences
Learning algorithms
Low cost
Machine learning
Measurement methods
multidisciplinary
Organic compounds
Science
Science (multidisciplinary)
Sensor arrays
Substrates
VOCs
Volatile organic compounds
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Summary:Understanding body malodour in a measurable manner is essential for developing personal care products. Body malodour is the result of bodily secretion of a highly complex mixture of volatile organic compounds. Current body malodour measurement methods are manual, time consuming and costly, requiring an expert panel of assessors to assign a malodour score to each human test subject. This article proposes a technology-based solution to automate this task by developing a custom-designed malodour score classification system comprising an electronic nose sensor array, a sensor readout interface and a machine learning hardware fabricated on low-cost flexible substrates. The proposed flexible integrated smart system is to augment the expert panel by acting like a panel assessor but could ultimately replace the panel to reduce the test and measurement costs. We demonstrate that it can classify malodour scores as good as or even better than half of the assessors on the expert panel. Designing machine learning hardware on flexible substrates is promising for several applications. Here, the authors propose an integrated smart system built with low-cost flexible electronics components for classifying human malodour, and demonstrates that the proposed system scores malodour as good as expert human assessors.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-023-36104-z