Malodour classification with low-cost flexible electronics

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作者
Emre Ozer
Jedrzej Kufel
John Biggs
Anjit Rana
Francisco J. Rodriguez
Thomas Lee-Clark
Antony Sou
Catherine Ramsdale
Scott White
Suresh Kumar Garlapati
Palaniappan Valliappan
Aiman Rahmanudin
Venuskrishnan Komanduri
Glenn Sunley Saez
Sankara Gollu
Gavin Brown
Piotr Dudek
Krishna C. Persaud
Michael L. Turner
Stephanie Murray
Susan Bates
Robert Treloar
Brian Newby
Jane Ford
机构
[1] Pragmatic Semiconductor,Indian Institute of Technology Hyderabad, Department of Materials Science and Metallurgical Engineering
[2] Arm,undefined
[3] Indian Institute of Technology Hyderabad,undefined
[4] University of Manchester,undefined
[5] University of Manchester,undefined
[6] Unilever,undefined
[7] Port Sunlight Lab,undefined
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摘要
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.
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