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Data set from gas sensor array under flow modulation.

Andrey Ziyatdinov1, Jordi Fonollosa2, Luis Fernández3

  • 1B2SLab, Department of ESAII, Universitat Politenica de Catalunya, Pau Gargallo 5, Barcelona, Spain ; Centro de Investigacion Biomedica en Red en Bioingenierıa, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona, Spain.

Data in Brief
|July 29, 2015
PubMed
Summary
This summary is machine-generated.

Active sniffing, or sampling odors, is crucial for the olfactory system. This study shares data from an artificial nose, revealing high-frequency signals linked to respiration, motivating further research into active sampling strategies.

Keywords:
BiomimeticsEarly detectionFlow modulationGas sensor arrayMOX sensorRespirationSniffing

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Area of Science:

  • Neuroscience
  • Artificial Intelligence
  • Sensor Technology

Background:

  • Active sniffing, or odor sampling, is increasingly recognized for its importance in the olfactory system, particularly for detecting novel odorants.
  • The computational benefits of high-frequency sampling in olfaction remain largely unexplored.
  • This work aims to provide data to stimulate research into active sampling strategies.

Purpose of the Study:

  • To share data from an artificial olfactory system designed to investigate active sampling strategies.
  • To provide a dataset for analyzing the role of respiration-like flow modulation in gas sensing.

Main Methods:

  • An artificial olfactory system with 16 Metal Oxide Semiconductor (MOX) gas sensors was employed.
  • A custom setup with an external mechanical ventilator mimicked biological respiration cycles to modulate gas flow.
  • Data were collected for 58 samples across 12 gas classes, comprising binary mixtures of acetone and ethanol in air.

Main Results:

  • Time-series data revealed two dominant frequency bands: a low-frequency band corresponding to conventional sensor responses and a high-frequency band with a harmonic at the respiration frequency.
  • The high-frequency signal component is directly linked to the emulated biological respiration cycle.

Conclusions:

  • The presented dataset, featuring gas sensor array data under flow modulation, offers valuable insights into olfactory sensing dynamics.
  • The findings highlight the presence and significance of high-frequency signals related to active sampling, driven by respiration emulation.
  • The data and associated code are publicly available to encourage further research in artificial olfaction and active sensing strategies.