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Related Concept Videos

Olfaction01:25

Olfaction

44.7K
The sense of smell is achieved through the activities of the olfactory system. It starts when an airborne odorant enters the nasal cavity and reaches olfactory epithelium (OE). The OE is protected by a thin layer of mucus, which also serves the purpose of dissolving more complex compounds into simpler chemical odorants. The size of the OE and the density of sensory neurons varies among species; in humans, the OE is only about 9-10 cm2.
The olfactory receptors are embedded in the cilia of the...
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Related Experiment Video

Updated: Aug 10, 2025

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization
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Malodour classification with low-cost flexible electronics.

Emre Ozer1, Jedrzej Kufel2, John Biggs2,3

  • 1Pragmatic Semiconductor, 400 Cambridge Science Park, Milton Road, Cambridge, CB4 0WH, UK. eozer@pragmaticsemi.com.

Nature Communications
|February 11, 2023
PubMed
Summary
This summary is machine-generated.

A new electronic nose system automates body malodour measurement, offering a cost-effective alternative to human expert panels. This smart technology accurately classifies malodour scores, potentially replacing traditional, time-consuming methods.

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Area of Science:

  • Analytical Chemistry
  • Biotechnology
  • Sensor Technology

Background:

  • Body malodour arises from complex volatile organic compounds in bodily secretions.
  • Current measurement methods rely on subjective, time-intensive, and expensive expert panels.
  • Objective and automated malodour assessment is crucial for personal care product development.

Purpose of the Study:

  • To develop an automated, technology-based system for classifying body malodour scores.
  • To create a cost-effective solution that can augment or replace human expert panels.
  • To integrate an electronic nose, sensor interface, and machine learning on flexible substrates.

Main Methods:

  • Fabrication of a custom-designed electronic nose sensor array on low-cost flexible substrates.
  • Development of a sensor readout interface and machine learning hardware.
  • Implementation of a malodour score classification system using the integrated smart device.

Main Results:

  • The proposed system successfully automates the classification of body malodour.
  • The technology-based system demonstrates performance comparable to or exceeding half of the human expert panel assessors.
  • The flexible integrated smart system offers a potential reduction in testing and measurement costs.

Conclusions:

  • An automated electronic nose system can effectively classify body malodour.
  • This technology provides a viable, cost-efficient alternative to traditional expert panel assessments.
  • The developed system paves the way for more objective and scalable malodour evaluation in personal care industries.